{smcl}
{txt}{sf}{ul off}{.-}
      name:  {res}<unnamed>
       {txt}log:  {res}C:\lSMS ISA\dofile\Submission\S1_S9_and_S19.smcl
  {txt}log type:  {res}smcl
 {txt}opened on:  {res} 5 Apr 2024, 11:00:11
{txt}
{com}. use  NER_panel_data.dta, clear
{txt}
{com}. gen country=1
{txt}
{com}. append using NIGERIA_panel_data.dta
{txt}
{com}. replace country=2 if country ==.
{txt}(18,592 real changes made)

{com}. 
. append using ETHIOPIA_panel_data.dta
{txt}
{com}. replace country=3 if country ==.
{txt}(13,511 real changes made)

{com}. 
. append using UGA_panel_data.dta
{txt}
{com}. replace country=4 if country ==.
{txt}(20,313 real changes made)

{com}. 
. append using TZA_panel_data.dta
{txt}
{com}. replace country=5 if country ==.
{txt}(21,117 real changes made)

{com}. 
. append using MWI_panel_data.dta
{txt}
{com}. replace country=6 if country ==.
{txt}(9,163 real changes made)

{com}. 
. xtset HHID_panel year
{res}{txt}{col 8}panel variable:  {res}HHID_panel (unbalanced)
{txt}{col 9}time variable:  {res}{col 25}year, 2008 to 2019, but with gaps
{txt}{col 17}delta:  {res}1 unit
{txt}
{com}. 
. label define country 1 "Niger" 2 "Nigeria" 3 "Ethiopia" 4 "Uganda" 5 "Tanzania" 6 "Malawi"
{txt}
{com}. label values country country
{txt}
{com}. 
. 
. 
. foreach x of varlist hhsize dependent_share head_age female_head head_read  motobike phone  electricity wagejob enterprise weather_shock  plot_area other_crop hdd9 pdd9 no_species{c -(}
{txt}  2{com}. egen `x'_mean=mean(`x'), by(HHID_panel)
{txt}  3{com}. {c )-}
{txt}
{com}. tab year, generate(year_)

       {txt}year {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
       2008 {c |}{res}      3,176        3.54        3.54
{txt}       2009 {c |}{res}      2,837        3.16        6.70
{txt}       2010 {c |}{res}     12,719       14.17       20.87
{txt}       2011 {c |}{res}     10,467       11.66       32.54
{txt}       2012 {c |}{res}      9,429       10.51       43.04
{txt}       2013 {c |}{res}     10,027       11.17       54.22
{txt}       2014 {c |}{res}      7,298        8.13       62.35
{txt}       2015 {c |}{res}     12,323       13.73       76.08
{txt}       2016 {c |}{res}      2,447        2.73       78.81
{txt}       2018 {c |}{res}      7,615        8.49       87.29
{txt}       2019 {c |}{res}     11,404       12.71      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}     89,742      100.00
{txt}
{com}. global year_NIGER year_4
{txt}
{com}. global year_NIGERIA year_3 year_5 year_8
{txt}
{com}. global year_ETHIOPIA year_6
{txt}
{com}. global year_UGANDA   year_3 year_4 year_6 year_8 year_10
{txt}
{com}. global year_TANZANIA year_1 year_5 year_7
{txt}
{com}. global year_MALAWI year_3 year_6 
{txt}
{com}. global xlist hhsize dependent_share head_age female_head head_read  motobike phone  electricity wagejob enterprise weather_shock  plot_area other_crop  motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean  
{txt}
{com}. 
. 
. 
. 
. ********************************************************************************
. *                              Table S1                                        *
. ********************************************************************************
. eststo clear
{txt}
{com}. xtreg hdd9  no_species   $xlist  no_species_mean i.country i.year  , cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    89,742
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}    36,644

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0269                                         {txt}min = {res}         1
{txt}     between = {res}0.3549                                         {txt}avg = {res}       2.4
{txt}     overall = {res}0.2842                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}35{txt})     =  {res} 26961.43
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:36,644} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}no_species {c |}{col 18}{res}{space 2} .0443685{col 30}{space 2} .0028497{col 41}{space 1}   15.57{col 50}{space 3}0.000{col 58}{space 4} .0387831{col 71}{space 3} .0499538
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} -.002285{col 30}{space 2} .0022411{col 41}{space 1}   -1.02{col 50}{space 3}0.308{col 58}{space 4}-.0066775{col 71}{space 3} .0021075
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0719461{col 30}{space 2} .0241382{col 41}{space 1}    2.98{col 50}{space 3}0.003{col 58}{space 4} .0246361{col 71}{space 3} .1192561
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0005157{col 30}{space 2} .0004112{col 41}{space 1}    1.25{col 50}{space 3}0.210{col 58}{space 4}-.0002903{col 71}{space 3} .0013217
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0485595{col 30}{space 2} .0144281{col 41}{space 1}    3.37{col 50}{space 3}0.001{col 58}{space 4}  .020281{col 71}{space 3} .0768381
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3001698{col 30}{space 2}  .013424{col 41}{space 1}   22.36{col 50}{space 3}0.000{col 58}{space 4} .2738592{col 71}{space 3} .3264804
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1242362{col 30}{space 2} .0252541{col 41}{space 1}    4.92{col 50}{space 3}0.000{col 58}{space 4} .0747391{col 71}{space 3} .1737333
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2185919{col 30}{space 2} .0173342{col 41}{space 1}   12.61{col 50}{space 3}0.000{col 58}{space 4} .1846175{col 71}{space 3} .2525663
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1819554{col 30}{space 2} .0199802{col 41}{space 1}    9.11{col 50}{space 3}0.000{col 58}{space 4} .1427949{col 71}{space 3} .2211159
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1249443{col 30}{space 2} .0166514{col 41}{space 1}    7.50{col 50}{space 3}0.000{col 58}{space 4} .0923081{col 71}{space 3} .1575804
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2194709{col 30}{space 2}  .015602{col 41}{space 1}   14.07{col 50}{space 3}0.000{col 58}{space 4} .1888915{col 71}{space 3} .2500502
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0811529{col 30}{space 2} .0128192{col 41}{space 1}   -6.33{col 50}{space 3}0.000{col 58}{space 4}-.1062781{col 71}{space 3}-.0560277
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0005239{col 30}{space 2} .0009503{col 41}{space 1}    0.55{col 50}{space 3}0.581{col 58}{space 4}-.0013386{col 71}{space 3} .0023864
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0646104{col 30}{space 2} .0158448{col 41}{space 1}    4.08{col 50}{space 3}0.000{col 58}{space 4} .0335552{col 71}{space 3} .0956656
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0744849{col 30}{space 2} .0343454{col 41}{space 1}    2.17{col 50}{space 3}0.030{col 58}{space 4} .0071692{col 71}{space 3} .1418006
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .5433875{col 30}{space 2} .0254747{col 41}{space 1}   21.33{col 50}{space 3}0.000{col 58}{space 4} .4934581{col 71}{space 3} .5933169
{txt}electricity_mean {c |}{col 18}{res}{space 2} .6815034{col 30}{space 2} .0271937{col 41}{space 1}   25.06{col 50}{space 3}0.000{col 58}{space 4} .6282048{col 71}{space 3} .7348019
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .2352794{col 30}{space 2} .0246578{col 41}{space 1}    9.54{col 50}{space 3}0.000{col 58}{space 4}  .186951{col 71}{space 3} .2836078
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .1860975{col 30}{space 2} .0221543{col 41}{space 1}    8.40{col 50}{space 3}0.000{col 58}{space 4} .1426758{col 71}{space 3} .2295192
{txt}{space 1}no_species_mean {c |}{col 18}{res}{space 2}-.0213853{col 30}{space 2} .0035172{col 41}{space 1}   -6.08{col 50}{space 3}0.000{col 58}{space 4} -.028279{col 71}{space 3}-.0144917
{txt}{space 16} {c |}
{space 9}country {c |}
{space 8}Nigeria  {c |}{col 18}{res}{space 2}-.2932313{col 30}{space 2} .0295588{col 41}{space 1}   -9.92{col 50}{space 3}0.000{col 58}{space 4}-.3511656{col 71}{space 3}-.2352971
{txt}{space 7}Ethiopia  {c |}{col 18}{res}{space 2}-1.358575{col 30}{space 2} .0292904{col 41}{space 1}  -46.38{col 50}{space 3}0.000{col 58}{space 4}-1.415983{col 71}{space 3}-1.301167
{txt}{space 9}Uganda  {c |}{col 18}{res}{space 2}-.3556034{col 30}{space 2} .0289791{col 41}{space 1}  -12.27{col 50}{space 3}0.000{col 58}{space 4}-.4124015{col 71}{space 3}-.2988053
{txt}{space 7}Tanzania  {c |}{col 18}{res}{space 2}-.1726939{col 30}{space 2} .0277016{col 41}{space 1}   -6.23{col 50}{space 3}0.000{col 58}{space 4} -.226988{col 71}{space 3}-.1183997
{txt}{space 9}Malawi  {c |}{col 18}{res}{space 2} .7107227{col 30}{space 2} .0336557{col 41}{space 1}   21.12{col 50}{space 3}0.000{col 58}{space 4} .6447588{col 71}{space 3} .7766866
{txt}{space 16} {c |}
{space 12}year {c |}
{space 11}2009  {c |}{col 18}{res}{space 2}-.2615948{col 30}{space 2} .0385206{col 41}{space 1}   -6.79{col 50}{space 3}0.000{col 58}{space 4}-.3370938{col 71}{space 3}-.1860959
{txt}{space 11}2010  {c |}{col 18}{res}{space 2}-.0710649{col 30}{space 2} .0276785{col 41}{space 1}   -2.57{col 50}{space 3}0.010{col 58}{space 4}-.1253138{col 71}{space 3}-.0168161
{txt}{space 11}2011  {c |}{col 18}{res}{space 2} .0286766{col 30}{space 2} .0318984{col 41}{space 1}    0.90{col 50}{space 3}0.369{col 58}{space 4} -.033843{col 71}{space 3} .0911963
{txt}{space 11}2012  {c |}{col 18}{res}{space 2}-.0095074{col 30}{space 2} .0280498{col 41}{space 1}   -0.34{col 50}{space 3}0.735{col 58}{space 4} -.064484{col 71}{space 3} .0454691
{txt}{space 11}2013  {c |}{col 18}{res}{space 2} .0421374{col 30}{space 2} .0317725{col 41}{space 1}    1.33{col 50}{space 3}0.185{col 58}{space 4}-.0201355{col 71}{space 3} .1044104
{txt}{space 11}2014  {c |}{col 18}{res}{space 2}-.0810557{col 30}{space 2} .0318817{col 41}{space 1}   -2.54{col 50}{space 3}0.011{col 58}{space 4}-.1435427{col 71}{space 3}-.0185688
{txt}{space 11}2015  {c |}{col 18}{res}{space 2} .1334589{col 30}{space 2} .0306383{col 41}{space 1}    4.36{col 50}{space 3}0.000{col 58}{space 4} .0734089{col 71}{space 3} .1935089
{txt}{space 11}2016  {c |}{col 18}{res}{space 2}-.2460099{col 30}{space 2} .0423465{col 41}{space 1}   -5.81{col 50}{space 3}0.000{col 58}{space 4}-.3290074{col 71}{space 3}-.1630123
{txt}{space 11}2018  {c |}{col 18}{res}{space 2} .3827753{col 30}{space 2} .0329631{col 41}{space 1}   11.61{col 50}{space 3}0.000{col 58}{space 4} .3181687{col 71}{space 3} .4473818
{txt}{space 11}2019  {c |}{col 18}{res}{space 2}-.1022424{col 30}{space 2} .0301381{col 41}{space 1}   -3.39{col 50}{space 3}0.001{col 58}{space 4} -.161312{col 71}{space 3}-.0431728
{txt}{space 16} {c |}
{space 11}_cons {c |}{col 18}{res}{space 2} 4.485908{col 30}{space 2} .0457436{col 41}{space 1}   98.07{col 50}{space 3}0.000{col 58}{space 4} 4.396252{col 71}{space 3} 4.575564
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res}  .8149875
         {txt}sigma_e {c |} {res} 1.2559737
             {txt}rho {c |} {res} .29629841{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est1
{txt}
{com}. 
. 
. xtreg hdd9  no_species   $xlist  no_species_mean $year_ETHIOPIA if country==3, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    13,511
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     5,436

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0214                                         {txt}min = {res}         1
{txt}     between = {res}0.3701                                         {txt}avg = {res}       2.5
{txt}     overall = {res}0.2576                                         {txt}max = {res}         3

                                                {txt}Wald chi2({res}21{txt})     =  {res}  3484.36
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:5,436} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}no_species {c |}{col 18}{res}{space 2} .0166213{col 30}{space 2} .0055063{col 41}{space 1}    3.02{col 50}{space 3}0.003{col 58}{space 4} .0058293{col 71}{space 3} .0274134
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0506938{col 30}{space 2}  .007001{col 41}{space 1}    7.24{col 50}{space 3}0.000{col 58}{space 4} .0369721{col 71}{space 3} .0644154
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0147286{col 30}{space 2} .0539529{col 41}{space 1}   -0.27{col 50}{space 3}0.785{col 58}{space 4}-.1204744{col 71}{space 3} .0910172
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0028529{col 30}{space 2} .0009473{col 41}{space 1}   -3.01{col 50}{space 3}0.003{col 58}{space 4}-.0047096{col 71}{space 3}-.0009962
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0148551{col 30}{space 2} .0331161{col 41}{space 1}   -0.45{col 50}{space 3}0.654{col 58}{space 4}-.0797615{col 71}{space 3} .0500513
{txt}{space 7}head_read {c |}{col 18}{res}{space 2}  .405636{col 30}{space 2} .0301005{col 41}{space 1}   13.48{col 50}{space 3}0.000{col 58}{space 4} .3466402{col 71}{space 3} .4646319
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}-.1238802{col 30}{space 2} .1319335{col 41}{space 1}   -0.94{col 50}{space 3}0.348{col 58}{space 4}-.3824652{col 71}{space 3} .1347048
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1960387{col 30}{space 2}  .036964{col 41}{space 1}    5.30{col 50}{space 3}0.000{col 58}{space 4} .1235907{col 71}{space 3} .2684868
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1532508{col 30}{space 2} .0451367{col 41}{space 1}    3.40{col 50}{space 3}0.001{col 58}{space 4} .0647844{col 71}{space 3} .2417171
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}-.0349639{col 30}{space 2}   .05357{col 41}{space 1}   -0.65{col 50}{space 3}0.514{col 58}{space 4}-.1399591{col 71}{space 3} .0700313
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2084507{col 30}{space 2} .0471412{col 41}{space 1}    4.42{col 50}{space 3}0.000{col 58}{space 4} .1160557{col 71}{space 3} .3008458
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1665288{col 30}{space 2} .0294391{col 41}{space 1}   -5.66{col 50}{space 3}0.000{col 58}{space 4}-.2242283{col 71}{space 3}-.1088293
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}  .007588{col 30}{space 2}  .003466{col 41}{space 1}    2.19{col 50}{space 3}0.029{col 58}{space 4} .0007947{col 71}{space 3} .0143812
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}  .222695{col 30}{space 2} .0333524{col 41}{space 1}    6.68{col 50}{space 3}0.000{col 58}{space 4} .1573254{col 71}{space 3} .2880646
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} 1.149641{col 30}{space 2} .2152657{col 41}{space 1}    5.34{col 50}{space 3}0.000{col 58}{space 4} .7277277{col 71}{space 3} 1.571554
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .5229237{col 30}{space 2} .0562509{col 41}{space 1}    9.30{col 50}{space 3}0.000{col 58}{space 4} .4126739{col 71}{space 3} .6331734
{txt}electricity_mean {c |}{col 18}{res}{space 2} .6254583{col 30}{space 2} .0668855{col 41}{space 1}    9.35{col 50}{space 3}0.000{col 58}{space 4} .4943651{col 71}{space 3} .7565515
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}   .48054{col 30}{space 2} .0811811{col 41}{space 1}    5.92{col 50}{space 3}0.000{col 58}{space 4} .3214279{col 71}{space 3} .6396521
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .0884969{col 30}{space 2} .0598379{col 41}{space 1}    1.48{col 50}{space 3}0.139{col 58}{space 4}-.0287832{col 71}{space 3} .2057769
{txt}{space 1}no_species_mean {c |}{col 18}{res}{space 2}  .001267{col 30}{space 2} .0068525{col 41}{space 1}    0.18{col 50}{space 3}0.853{col 58}{space 4}-.0121636{col 71}{space 3} .0146977
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}-.1918565{col 30}{space 2} .0216135{col 41}{space 1}   -8.88{col 50}{space 3}0.000{col 58}{space 4}-.2342182{col 71}{space 3}-.1494949
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 3.225873{col 30}{space 2} .0667081{col 41}{space 1}   48.36{col 50}{space 3}0.000{col 58}{space 4} 3.095127{col 71}{space 3} 3.356618
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res}  .7621519
         {txt}sigma_e {c |} {res} 1.1132581
             {txt}rho {c |} {res} .31912394{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est2
{txt}
{com}. 
. xtreg hdd9  no_species   $xlist  no_species_mean $year_MALAWI if country==6, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     9,163
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     3,447

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0420                                         {txt}min = {res}         1
{txt}     between = {res}0.3713                                         {txt}avg = {res}       2.7
{txt}     overall = {res}0.2949                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}22{txt})     =  {res}  3141.98
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,447} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}no_species {c |}{col 18}{res}{space 2} .0899114{col 30}{space 2} .0098858{col 41}{space 1}    9.09{col 50}{space 3}0.000{col 58}{space 4} .0705355{col 71}{space 3} .1092873
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0116703{col 30}{space 2} .0087587{col 41}{space 1}   -1.33{col 50}{space 3}0.183{col 58}{space 4} -.028837{col 71}{space 3} .0054963
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.3331084{col 30}{space 2} .0732846{col 41}{space 1}   -4.55{col 50}{space 3}0.000{col 58}{space 4}-.4767436{col 71}{space 3}-.1894732
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0032715{col 30}{space 2} .0012689{col 41}{space 1}   -2.58{col 50}{space 3}0.010{col 58}{space 4}-.0057584{col 71}{space 3}-.0007845
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0998213{col 30}{space 2} .0419066{col 41}{space 1}   -2.38{col 50}{space 3}0.017{col 58}{space 4}-.1819567{col 71}{space 3}-.0176858
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2942003{col 30}{space 2} .0447884{col 41}{space 1}    6.57{col 50}{space 3}0.000{col 58}{space 4} .2064166{col 71}{space 3} .3819841
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}  .233312{col 30}{space 2} .1365571{col 41}{space 1}    1.71{col 50}{space 3}0.088{col 58}{space 4}-.0343349{col 71}{space 3}  .500959
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2555796{col 30}{space 2} .0526945{col 41}{space 1}    4.85{col 50}{space 3}0.000{col 58}{space 4} .1523002{col 71}{space 3}  .358859
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .4475193{col 30}{space 2} .0857579{col 41}{space 1}    5.22{col 50}{space 3}0.000{col 58}{space 4}  .279437{col 71}{space 3} .6156016
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1818363{col 30}{space 2} .0563267{col 41}{space 1}    3.23{col 50}{space 3}0.001{col 58}{space 4}  .071438{col 71}{space 3} .2922347
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2616892{col 30}{space 2} .0413364{col 41}{space 1}    6.33{col 50}{space 3}0.000{col 58}{space 4} .1806713{col 71}{space 3}  .342707
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1917017{col 30}{space 2} .0327404{col 41}{space 1}   -5.86{col 50}{space 3}0.000{col 58}{space 4}-.2558716{col 71}{space 3}-.1275318
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0135831{col 30}{space 2} .0262597{col 41}{space 1}    0.52{col 50}{space 3}0.605{col 58}{space 4}-.0378849{col 71}{space 3} .0650511
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.0546488{col 30}{space 2} .0484106{col 41}{space 1}   -1.13{col 50}{space 3}0.259{col 58}{space 4}-.1495318{col 71}{space 3} .0402341
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .3249635{col 30}{space 2}  .212399{col 41}{space 1}    1.53{col 50}{space 3}0.126{col 58}{space 4}-.0913308{col 71}{space 3} .7412579
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .4628961{col 30}{space 2} .0761613{col 41}{space 1}    6.08{col 50}{space 3}0.000{col 58}{space 4} .3136228{col 71}{space 3} .6121695
{txt}electricity_mean {c |}{col 18}{res}{space 2}  .728563{col 30}{space 2} .1097915{col 41}{space 1}    6.64{col 50}{space 3}0.000{col 58}{space 4} .5133756{col 71}{space 3} .9437504
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .3821026{col 30}{space 2} .0790402{col 41}{space 1}    4.83{col 50}{space 3}0.000{col 58}{space 4} .2271866{col 71}{space 3} .5370185
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .3380611{col 30}{space 2} .0675557{col 41}{space 1}    5.00{col 50}{space 3}0.000{col 58}{space 4} .2056543{col 71}{space 3} .4704679
{txt}{space 1}no_species_mean {c |}{col 18}{res}{space 2}-.0564073{col 30}{space 2} .0136416{col 41}{space 1}   -4.13{col 50}{space 3}0.000{col 58}{space 4}-.0831444{col 71}{space 3}-.0296701
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2} .1199118{col 30}{space 2}  .042024{col 41}{space 1}    2.85{col 50}{space 3}0.004{col 58}{space 4} .0375462{col 71}{space 3} .2022773
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .0671032{col 30}{space 2} .0350129{col 41}{space 1}    1.92{col 50}{space 3}0.055{col 58}{space 4}-.0015208{col 71}{space 3} .1357273
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 5.323738{col 30}{space 2} .0863889{col 41}{space 1}   61.63{col 50}{space 3}0.000{col 58}{space 4} 5.154419{col 71}{space 3} 5.493057
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .69442314
         {txt}sigma_e {c |} {res} 1.3052971
             {txt}rho {c |} {res} .22059386{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est3
{txt}
{com}. 
. 
. xtreg hdd9  no_species   $xlist  no_species_mean $year_NIGER if country==1, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     7,046
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     4,069

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0443                                         {txt}min = {res}         1
{txt}     between = {res}0.2381                                         {txt}avg = {res}       1.7
{txt}     overall = {res}0.1925                                         {txt}max = {res}         2

                                                {txt}Wald chi2({res}21{txt})     =  {res}  1604.96
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:4,069} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}no_species {c |}{col 18}{res}{space 2} .1402652{col 30}{space 2} .0176414{col 41}{space 1}    7.95{col 50}{space 3}0.000{col 58}{space 4} .1056887{col 71}{space 3} .1748418
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0143472{col 30}{space 2} .0064858{col 41}{space 1}    2.21{col 50}{space 3}0.027{col 58}{space 4} .0016353{col 71}{space 3} .0270591
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0394669{col 30}{space 2} .0962628{col 41}{space 1}   -0.41{col 50}{space 3}0.682{col 58}{space 4}-.2281385{col 71}{space 3} .1492047
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0029258{col 30}{space 2} .0013876{col 41}{space 1}    2.11{col 50}{space 3}0.035{col 58}{space 4} .0002061{col 71}{space 3} .0056455
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .1077797{col 30}{space 2} .0577617{col 41}{space 1}    1.87{col 50}{space 3}0.062{col 58}{space 4}-.0054312{col 71}{space 3} .2209906
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3395085{col 30}{space 2} .0440964{col 41}{space 1}    7.70{col 50}{space 3}0.000{col 58}{space 4} .2530812{col 71}{space 3} .4259357
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2458747{col 30}{space 2} .0966195{col 41}{space 1}    2.54{col 50}{space 3}0.011{col 58}{space 4}  .056504{col 71}{space 3} .4352454
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0926715{col 30}{space 2} .0743259{col 41}{space 1}    1.25{col 50}{space 3}0.212{col 58}{space 4}-.0530046{col 71}{space 3} .2383477
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .2137803{col 30}{space 2} .1067788{col 41}{space 1}    2.00{col 50}{space 3}0.045{col 58}{space 4} .0044977{col 71}{space 3} .4230629
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2020572{col 30}{space 2} .0848793{col 41}{space 1}    2.38{col 50}{space 3}0.017{col 58}{space 4} .0356969{col 71}{space 3} .3684176
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}-.1981656{col 30}{space 2} .0654339{col 41}{space 1}   -3.03{col 50}{space 3}0.002{col 58}{space 4}-.3264137{col 71}{space 3}-.0699175
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1329074{col 30}{space 2} .0450631{col 41}{space 1}   -2.95{col 50}{space 3}0.003{col 58}{space 4}-.2212295{col 71}{space 3}-.0445853
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0014096{col 30}{space 2} .0015982{col 41}{space 1}   -0.88{col 50}{space 3}0.378{col 58}{space 4} -.004542{col 71}{space 3} .0017227
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1490097{col 30}{space 2} .2200744{col 41}{space 1}    0.68{col 50}{space 3}0.498{col 58}{space 4}-.2823283{col 71}{space 3} .5803477
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1072688{col 30}{space 2} .1187873{col 41}{space 1}    0.90{col 50}{space 3}0.367{col 58}{space 4}  -.12555{col 71}{space 3} .3400876
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .3380503{col 30}{space 2} .0917087{col 41}{space 1}    3.69{col 50}{space 3}0.000{col 58}{space 4} .1583045{col 71}{space 3}  .517796
{txt}electricity_mean {c |}{col 18}{res}{space 2}  .524161{col 30}{space 2} .1249025{col 41}{space 1}    4.20{col 50}{space 3}0.000{col 58}{space 4} .2793567{col 71}{space 3} .7689653
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .2022936{col 30}{space 2} .1044315{col 41}{space 1}    1.94{col 50}{space 3}0.053{col 58}{space 4}-.0023883{col 71}{space 3} .4069755
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}  .460175{col 30}{space 2} .0809448{col 41}{space 1}    5.69{col 50}{space 3}0.000{col 58}{space 4} .3015262{col 71}{space 3} .6188239
{txt}{space 1}no_species_mean {c |}{col 18}{res}{space 2} -.155864{col 30}{space 2} .0199988{col 41}{space 1}   -7.79{col 50}{space 3}0.000{col 58}{space 4}-.1950609{col 71}{space 3}-.1166672
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2} .2440088{col 30}{space 2} .0363028{col 41}{space 1}    6.72{col 50}{space 3}0.000{col 58}{space 4} .1728566{col 71}{space 3} .3151609
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.572957{col 30}{space 2} .1047694{col 41}{space 1}   43.65{col 50}{space 3}0.000{col 58}{space 4} 4.367613{col 71}{space 3} 4.778302
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .62305345
         {txt}sigma_e {c |} {res} 1.3666293
             {txt}rho {c |} {res} .17208235{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est4
{txt}
{com}. 
. 
. xtreg hdd9  no_species   $xlist  no_species_mean $year_NIGERIA if country==2, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    18,592
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     8,222

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0392                                         {txt}min = {res}         1
{txt}     between = {res}0.3106                                         {txt}avg = {res}       2.3
{txt}     overall = {res}0.2617                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}23{txt})     =  {res}  4908.63
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:8,222} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}no_species {c |}{col 18}{res}{space 2} .0471703{col 30}{space 2} .0081724{col 41}{space 1}    5.77{col 50}{space 3}0.000{col 58}{space 4} .0311527{col 71}{space 3} .0631879
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} -.020121{col 30}{space 2} .0044888{col 41}{space 1}   -4.48{col 50}{space 3}0.000{col 58}{space 4}-.0289188{col 71}{space 3}-.0113231
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .1331588{col 30}{space 2} .0489675{col 41}{space 1}    2.72{col 50}{space 3}0.007{col 58}{space 4} .0371842{col 71}{space 3} .2291334
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0049115{col 30}{space 2}    .0009{col 41}{space 1}    5.46{col 50}{space 3}0.000{col 58}{space 4} .0031475{col 71}{space 3} .0066755
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .2093415{col 30}{space 2} .0352523{col 41}{space 1}    5.94{col 50}{space 3}0.000{col 58}{space 4} .1402483{col 71}{space 3} .2784348
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .1934741{col 30}{space 2} .0272279{col 41}{space 1}    7.11{col 50}{space 3}0.000{col 58}{space 4} .1401084{col 71}{space 3} .2468398
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0342251{col 30}{space 2} .0383678{col 41}{space 1}    0.89{col 50}{space 3}0.372{col 58}{space 4}-.0409744{col 71}{space 3} .1094247
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1843987{col 30}{space 2} .0382266{col 41}{space 1}    4.82{col 50}{space 3}0.000{col 58}{space 4} .1094759{col 71}{space 3} .2593214
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0881066{col 30}{space 2} .0445719{col 41}{space 1}    1.98{col 50}{space 3}0.048{col 58}{space 4} .0007474{col 71}{space 3} .1754659
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2083799{col 30}{space 2} .0481205{col 41}{space 1}    4.33{col 50}{space 3}0.000{col 58}{space 4} .1140654{col 71}{space 3} .3026944
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2754478{col 30}{space 2} .0390961{col 41}{space 1}    7.05{col 50}{space 3}0.000{col 58}{space 4} .1988208{col 71}{space 3} .3520747
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} .0062967{col 30}{space 2} .0467175{col 41}{space 1}    0.13{col 50}{space 3}0.893{col 58}{space 4} -.085268{col 71}{space 3} .0978614
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} -.006907{col 30}{space 2} .0060128{col 41}{space 1}   -1.15{col 50}{space 3}0.251{col 58}{space 4}-.0186918{col 71}{space 3} .0048779
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .3312306{col 30}{space 2} .0604439{col 41}{space 1}    5.48{col 50}{space 3}0.000{col 58}{space 4} .2127627{col 71}{space 3} .4496985
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}-.0114003{col 30}{space 2} .0531208{col 41}{space 1}   -0.21{col 50}{space 3}0.830{col 58}{space 4}-.1155151{col 71}{space 3} .0927144
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .8015068{col 30}{space 2} .0585994{col 41}{space 1}   13.68{col 50}{space 3}0.000{col 58}{space 4}  .686654{col 71}{space 3} .9163595
{txt}electricity_mean {c |}{col 18}{res}{space 2} .7937102{col 30}{space 2} .0576417{col 41}{space 1}   13.77{col 50}{space 3}0.000{col 58}{space 4} .6807345{col 71}{space 3} .9066859
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .2169979{col 30}{space 2} .0637748{col 41}{space 1}    3.40{col 50}{space 3}0.001{col 58}{space 4} .0920017{col 71}{space 3} .3419942
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.0234546{col 30}{space 2} .0511102{col 41}{space 1}   -0.46{col 50}{space 3}0.646{col 58}{space 4}-.1236287{col 71}{space 3} .0767195
{txt}{space 1}no_species_mean {c |}{col 18}{res}{space 2}-.0729979{col 30}{space 2} .0104846{col 41}{space 1}   -6.96{col 50}{space 3}0.000{col 58}{space 4}-.0935472{col 71}{space 3}-.0524485
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.5991942{col 30}{space 2} .0306746{col 41}{space 1}  -19.53{col 50}{space 3}0.000{col 58}{space 4}-.6593153{col 71}{space 3} -.539073
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2} -.506705{col 30}{space 2} .0308954{col 41}{space 1}  -16.40{col 50}{space 3}0.000{col 58}{space 4}-.5672589{col 71}{space 3}-.4461511
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2}-.3506558{col 30}{space 2} .0303754{col 41}{space 1}  -11.54{col 50}{space 3}0.000{col 58}{space 4}-.4101904{col 71}{space 3}-.2911211
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.644306{col 30}{space 2} .0743304{col 41}{space 1}   62.48{col 50}{space 3}0.000{col 58}{space 4} 4.498621{col 71}{space 3} 4.789991
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .85797448
         {txt}sigma_e {c |} {res} 1.2351846
             {txt}rho {c |} {res} .32545753{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est5
{txt}
{com}. 
. 
. xtreg hdd9  no_species   $xlist  no_species_mean $year_TANZANIA if country==5, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    21,117
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}    10,363

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0244                                         {txt}min = {res}         1
{txt}     between = {res}0.2175                                         {txt}avg = {res}       2.0
{txt}     overall = {res}0.1863                                         {txt}max = {res}         5

                                                {txt}Wald chi2({res}23{txt})     =  {res}  3757.04
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:10,363} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}no_species {c |}{col 18}{res}{space 2} .0576956{col 30}{space 2} .0055906{col 41}{space 1}   10.32{col 50}{space 3}0.000{col 58}{space 4} .0467383{col 71}{space 3} .0686529
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0049955{col 30}{space 2}  .004237{col 41}{space 1}   -1.18{col 50}{space 3}0.238{col 58}{space 4}-.0132998{col 71}{space 3} .0033089
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}  .099483{col 30}{space 2}  .050736{col 41}{space 1}    1.96{col 50}{space 3}0.050{col 58}{space 4} .0000424{col 71}{space 3} .1989237
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0011434{col 30}{space 2} .0008232{col 41}{space 1}   -1.39{col 50}{space 3}0.165{col 58}{space 4}-.0027569{col 71}{space 3} .0004701
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0697969{col 30}{space 2} .0276441{col 41}{space 1}    2.52{col 50}{space 3}0.012{col 58}{space 4} .0156155{col 71}{space 3} .1239784
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3057733{col 30}{space 2} .0286156{col 41}{space 1}   10.69{col 50}{space 3}0.000{col 58}{space 4} .2496877{col 71}{space 3} .3618589
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1841884{col 30}{space 2} .0592742{col 41}{space 1}    3.11{col 50}{space 3}0.002{col 58}{space 4}  .068013{col 71}{space 3} .3003637
{txt}{space 11}phone {c |}{col 18}{res}{space 2}  .307486{col 30}{space 2} .0396454{col 41}{space 1}    7.76{col 50}{space 3}0.000{col 58}{space 4} .2297825{col 71}{space 3} .3851896
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0811673{col 30}{space 2} .0426106{col 41}{space 1}    1.90{col 50}{space 3}0.057{col 58}{space 4}-.0023479{col 71}{space 3} .1646826
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1335962{col 30}{space 2}  .029948{col 41}{space 1}    4.46{col 50}{space 3}0.000{col 58}{space 4} .0748993{col 71}{space 3} .1922932
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2595765{col 30}{space 2} .0316425{col 41}{space 1}    8.20{col 50}{space 3}0.000{col 58}{space 4} .1975583{col 71}{space 3} .3215947
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1488398{col 30}{space 2} .0266399{col 41}{space 1}   -5.59{col 50}{space 3}0.000{col 58}{space 4}-.2010532{col 71}{space 3}-.0966265
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0019937{col 30}{space 2} .0019771{col 41}{space 1}    1.01{col 50}{space 3}0.313{col 58}{space 4}-.0018814{col 71}{space 3} .0058688
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.0627476{col 30}{space 2} .0306755{col 41}{space 1}   -2.05{col 50}{space 3}0.041{col 58}{space 4}-.1228706{col 71}{space 3}-.0026247
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .4859705{col 30}{space 2} .0762218{col 41}{space 1}    6.38{col 50}{space 3}0.000{col 58}{space 4} .3365785{col 71}{space 3} .6353625
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .4016056{col 30}{space 2} .0538522{col 41}{space 1}    7.46{col 50}{space 3}0.000{col 58}{space 4} .2960573{col 71}{space 3}  .507154
{txt}electricity_mean {c |}{col 18}{res}{space 2} .5470101{col 30}{space 2} .0545815{col 41}{space 1}   10.02{col 50}{space 3}0.000{col 58}{space 4} .4400323{col 71}{space 3} .6539878
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1189543{col 30}{space 2} .0424438{col 41}{space 1}    2.80{col 50}{space 3}0.005{col 58}{space 4}  .035766{col 71}{space 3} .2021427
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .2377005{col 30}{space 2} .0435131{col 41}{space 1}    5.46{col 50}{space 3}0.000{col 58}{space 4} .1524164{col 71}{space 3} .3229846
{txt}{space 1}no_species_mean {c |}{col 18}{res}{space 2}-.0291547{col 30}{space 2} .0065248{col 41}{space 1}   -4.47{col 50}{space 3}0.000{col 58}{space 4}-.0419431{col 71}{space 3}-.0163662
{txt}{space 10}year_1 {c |}{col 18}{res}{space 2} .0951978{col 30}{space 2} .0289431{col 41}{space 1}    3.29{col 50}{space 3}0.001{col 58}{space 4} .0384704{col 71}{space 3} .1519252
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2} .0944423{col 30}{space 2} .0243487{col 41}{space 1}    3.88{col 50}{space 3}0.000{col 58}{space 4} .0467198{col 71}{space 3} .1421648
{txt}{space 10}year_7 {c |}{col 18}{res}{space 2} .1118864{col 30}{space 2} .0272184{col 41}{space 1}    4.11{col 50}{space 3}0.000{col 58}{space 4} .0585393{col 71}{space 3} .1652335
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.379884{col 30}{space 2} .0619963{col 41}{space 1}   70.65{col 50}{space 3}0.000{col 58}{space 4} 4.258373{col 71}{space 3} 4.501394
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res}  .7949824
         {txt}sigma_e {c |} {res} 1.2490973
             {txt}rho {c |} {res} .28828811{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est6
{txt}
{com}. 
. xtreg hdd9  no_species   $xlist  no_species_mean  $year_UGANDA if country==4, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    20,313
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     5,107

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0464                                         {txt}min = {res}         1
{txt}     between = {res}0.2713                                         {txt}avg = {res}       4.0
{txt}     overall = {res}0.1877                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}25{txt})     =  {res}  2946.35
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:5,107} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}no_species {c |}{col 18}{res}{space 2}  .047658{col 30}{space 2} .0054543{col 41}{space 1}    8.74{col 50}{space 3}0.000{col 58}{space 4} .0369678{col 71}{space 3} .0583482
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0147358{col 30}{space 2} .0052129{col 41}{space 1}    2.83{col 50}{space 3}0.005{col 58}{space 4} .0045187{col 71}{space 3} .0249528
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .1616278{col 30}{space 2} .0553579{col 41}{space 1}    2.92{col 50}{space 3}0.004{col 58}{space 4} .0531282{col 71}{space 3} .2701274
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0014277{col 30}{space 2} .0009858{col 41}{space 1}   -1.45{col 50}{space 3}0.148{col 58}{space 4}-.0033598{col 71}{space 3} .0005044
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0665107{col 30}{space 2} .0318214{col 41}{space 1}    2.09{col 50}{space 3}0.037{col 58}{space 4} .0041419{col 71}{space 3} .1288796
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2659529{col 30}{space 2} .0314226{col 41}{space 1}    8.46{col 50}{space 3}0.000{col 58}{space 4} .2043657{col 71}{space 3} .3275401
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2268858{col 30}{space 2}  .050048{col 41}{space 1}    4.53{col 50}{space 3}0.000{col 58}{space 4} .1287934{col 71}{space 3} .3249782
{txt}{space 11}phone {c |}{col 18}{res}{space 2}  .257494{col 30}{space 2} .0338828{col 41}{space 1}    7.60{col 50}{space 3}0.000{col 58}{space 4}  .191085{col 71}{space 3} .3239031
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .3541301{col 30}{space 2} .0342232{col 41}{space 1}   10.35{col 50}{space 3}0.000{col 58}{space 4} .2870538{col 71}{space 3} .4212063
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}  .059779{col 30}{space 2} .0276811{col 41}{space 1}    2.16{col 50}{space 3}0.031{col 58}{space 4} .0055251{col 71}{space 3}  .114033
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .1891433{col 30}{space 2} .0284118{col 41}{space 1}    6.66{col 50}{space 3}0.000{col 58}{space 4} .1334573{col 71}{space 3} .2448294
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0168306{col 30}{space 2} .0236343{col 41}{space 1}   -0.71{col 50}{space 3}0.476{col 58}{space 4}-.0631531{col 71}{space 3} .0294918
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0011719{col 30}{space 2} .0011988{col 41}{space 1}    0.98{col 50}{space 3}0.328{col 58}{space 4}-.0011778{col 71}{space 3} .0035216
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.0520941{col 30}{space 2}   .02815{col 41}{space 1}   -1.85{col 50}{space 3}0.064{col 58}{space 4}-.1072671{col 71}{space 3} .0030788
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .2273368{col 30}{space 2} .0799668{col 41}{space 1}    2.84{col 50}{space 3}0.004{col 58}{space 4} .0706048{col 71}{space 3} .3840688
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}  .398057{col 30}{space 2} .0598042{col 41}{space 1}    6.66{col 50}{space 3}0.000{col 58}{space 4}  .280843{col 71}{space 3}  .515271
{txt}electricity_mean {c |}{col 18}{res}{space 2} .4687039{col 30}{space 2}  .064228{col 41}{space 1}    7.30{col 50}{space 3}0.000{col 58}{space 4} .3428193{col 71}{space 3} .5945885
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1472851{col 30}{space 2} .0530634{col 41}{space 1}    2.78{col 50}{space 3}0.006{col 58}{space 4} .0432827{col 71}{space 3} .2512875
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .3479567{col 30}{space 2} .0510073{col 41}{space 1}    6.82{col 50}{space 3}0.000{col 58}{space 4} .2479842{col 71}{space 3} .4479293
{txt}{space 1}no_species_mean {c |}{col 18}{res}{space 2}-.0007071{col 30}{space 2} .0076852{col 41}{space 1}   -0.09{col 50}{space 3}0.927{col 58}{space 4}-.0157698{col 71}{space 3} .0143556
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.1873422{col 30}{space 2} .0323652{col 41}{space 1}   -5.79{col 50}{space 3}0.000{col 58}{space 4}-.2507769{col 71}{space 3}-.1239076
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2}-.0527764{col 30}{space 2} .0304618{col 41}{space 1}   -1.73{col 50}{space 3}0.083{col 58}{space 4}-.1124804{col 71}{space 3} .0069275
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .3545908{col 30}{space 2} .0308456{col 41}{space 1}   11.50{col 50}{space 3}0.000{col 58}{space 4} .2941345{col 71}{space 3} .4150471
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2} .0892875{col 30}{space 2} .0306335{col 41}{space 1}    2.91{col 50}{space 3}0.004{col 58}{space 4}  .029247{col 71}{space 3}  .149328
{txt}{space 9}year_10 {c |}{col 18}{res}{space 2} .2966267{col 30}{space 2} .0291994{col 41}{space 1}   10.16{col 50}{space 3}0.000{col 58}{space 4}  .239397{col 71}{space 3} .3538564
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.002872{col 30}{space 2} .0800372{col 41}{space 1}   50.01{col 50}{space 3}0.000{col 58}{space 4} 3.846002{col 71}{space 3} 4.159742
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .86524939
         {txt}sigma_e {c |} {res} 1.2845376
             {txt}rho {c |} {res} .31211014{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est7
{txt}
{com}. 
. esttab using  S1.rtf, se replace star(* 0.1 ** 0.05 *** 0.01) cells (b(star fmt(%9.3f)) se (par(( )) fmt(%9.3f)))  stats(N r2_b  r2_w r2_o p, fmt(%4.0f %4.3f %4.3f %6.3f)) keep(no_species   $xlist  no_species_mean _cons)
{res}{txt}(note: file S1.rtf not found)
(output written to {browse  `"S1.rtf"'})

{com}. 
. 
. 
. ********************************************************************************
. *                              Table S2                                        *
. ********************************************************************************
. eststo clear
{txt}
{com}. 
. xtreg hdd9  pdd9   $xlist   pdd9_mean i.country i.year, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    89,742
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}    36,644

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0290                                         {txt}min = {res}         1
{txt}     between = {res}0.3561                                         {txt}avg = {res}       2.4
{txt}     overall = {res}0.2856                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}35{txt})     =  {res} 27347.26
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:36,644} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2}  .100046{col 30}{space 2} .0051959{col 41}{space 1}   19.25{col 50}{space 3}0.000{col 58}{space 4} .0898622{col 71}{space 3} .1102297
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0030401{col 30}{space 2} .0022275{col 41}{space 1}   -1.36{col 50}{space 3}0.172{col 58}{space 4} -.007406{col 71}{space 3} .0013258
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}  .065032{col 30}{space 2}   .02411{col 41}{space 1}    2.70{col 50}{space 3}0.007{col 58}{space 4} .0177772{col 71}{space 3} .1122868
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0004217{col 30}{space 2}   .00041{col 41}{space 1}    1.03{col 50}{space 3}0.304{col 58}{space 4}-.0003818{col 71}{space 3} .0012253
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0496982{col 30}{space 2} .0143935{col 41}{space 1}    3.45{col 50}{space 3}0.001{col 58}{space 4} .0214874{col 71}{space 3}  .077909
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3002783{col 30}{space 2} .0134006{col 41}{space 1}   22.41{col 50}{space 3}0.000{col 58}{space 4} .2740137{col 71}{space 3} .3265429
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1228612{col 30}{space 2} .0252171{col 41}{space 1}    4.87{col 50}{space 3}0.000{col 58}{space 4} .0734365{col 71}{space 3} .1722858
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2169943{col 30}{space 2} .0173222{col 41}{space 1}   12.53{col 50}{space 3}0.000{col 58}{space 4} .1830434{col 71}{space 3} .2509452
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1804894{col 30}{space 2}  .019958{col 41}{space 1}    9.04{col 50}{space 3}0.000{col 58}{space 4} .1413725{col 71}{space 3} .2196063
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1260233{col 30}{space 2} .0166278{col 41}{space 1}    7.58{col 50}{space 3}0.000{col 58}{space 4} .0934334{col 71}{space 3} .1586132
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2200247{col 30}{space 2} .0155761{col 41}{space 1}   14.13{col 50}{space 3}0.000{col 58}{space 4}  .189496{col 71}{space 3} .2505533
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0865284{col 30}{space 2} .0128051{col 41}{space 1}   -6.76{col 50}{space 3}0.000{col 58}{space 4} -.111626{col 71}{space 3}-.0614309
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0003881{col 30}{space 2} .0009502{col 41}{space 1}    0.41{col 50}{space 3}0.683{col 58}{space 4}-.0014743{col 71}{space 3} .0022504
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0966535{col 30}{space 2} .0148938{col 41}{space 1}    6.49{col 50}{space 3}0.000{col 58}{space 4} .0674622{col 71}{space 3} .1258448
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0706861{col 30}{space 2} .0343358{col 41}{space 1}    2.06{col 50}{space 3}0.040{col 58}{space 4} .0033892{col 71}{space 3}  .137983
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .5467516{col 30}{space 2} .0254487{col 41}{space 1}   21.48{col 50}{space 3}0.000{col 58}{space 4} .4968731{col 71}{space 3} .5966302
{txt}electricity_mean {c |}{col 18}{res}{space 2} .6966126{col 30}{space 2} .0272048{col 41}{space 1}   25.61{col 50}{space 3}0.000{col 58}{space 4} .6432923{col 71}{space 3}  .749933
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}  .240854{col 30}{space 2}  .024667{col 41}{space 1}    9.76{col 50}{space 3}0.000{col 58}{space 4} .1925076{col 71}{space 3} .2892004
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .1894021{col 30}{space 2} .0221414{col 41}{space 1}    8.55{col 50}{space 3}0.000{col 58}{space 4} .1460057{col 71}{space 3} .2327984
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.0503437{col 30}{space 2} .0067234{col 41}{space 1}   -7.49{col 50}{space 3}0.000{col 58}{space 4}-.0635213{col 71}{space 3}-.0371661
{txt}{space 16} {c |}
{space 9}country {c |}
{space 8}Nigeria  {c |}{col 18}{res}{space 2}-.3034848{col 30}{space 2} .0295445{col 41}{space 1}  -10.27{col 50}{space 3}0.000{col 58}{space 4}-.3613909{col 71}{space 3}-.2455787
{txt}{space 7}Ethiopia  {c |}{col 18}{res}{space 2}-1.372043{col 30}{space 2}   .02916{col 41}{space 1}  -47.05{col 50}{space 3}0.000{col 58}{space 4}-1.429196{col 71}{space 3}-1.314891
{txt}{space 9}Uganda  {c |}{col 18}{res}{space 2}-.3849754{col 30}{space 2} .0291919{col 41}{space 1}  -13.19{col 50}{space 3}0.000{col 58}{space 4}-.4421905{col 71}{space 3}-.3277604
{txt}{space 7}Tanzania  {c |}{col 18}{res}{space 2}-.1965689{col 30}{space 2} .0278902{col 41}{space 1}   -7.05{col 50}{space 3}0.000{col 58}{space 4}-.2512327{col 71}{space 3}-.1419051
{txt}{space 9}Malawi  {c |}{col 18}{res}{space 2} .6739114{col 30}{space 2} .0337996{col 41}{space 1}   19.94{col 50}{space 3}0.000{col 58}{space 4} .6076653{col 71}{space 3} .7401575
{txt}{space 16} {c |}
{space 12}year {c |}
{space 11}2009  {c |}{col 18}{res}{space 2}-.2256059{col 30}{space 2} .0385288{col 41}{space 1}   -5.86{col 50}{space 3}0.000{col 58}{space 4} -.301121{col 71}{space 3}-.1500909
{txt}{space 11}2010  {c |}{col 18}{res}{space 2}-.0506931{col 30}{space 2} .0276656{col 41}{space 1}   -1.83{col 50}{space 3}0.067{col 58}{space 4}-.1049168{col 71}{space 3} .0035305
{txt}{space 11}2011  {c |}{col 18}{res}{space 2} .0427377{col 30}{space 2} .0318888{col 41}{space 1}    1.34{col 50}{space 3}0.180{col 58}{space 4}-.0197632{col 71}{space 3} .1052386
{txt}{space 11}2012  {c |}{col 18}{res}{space 2} .0060608{col 30}{space 2}  .028045{col 41}{space 1}    0.22{col 50}{space 3}0.829{col 58}{space 4}-.0489064{col 71}{space 3}  .061028
{txt}{space 11}2013  {c |}{col 18}{res}{space 2} .0529548{col 30}{space 2}  .031712{col 41}{space 1}    1.67{col 50}{space 3}0.095{col 58}{space 4}-.0091995{col 71}{space 3} .1151091
{txt}{space 11}2014  {c |}{col 18}{res}{space 2}-.0722623{col 30}{space 2} .0318453{col 41}{space 1}   -2.27{col 50}{space 3}0.023{col 58}{space 4} -.134678{col 71}{space 3}-.0098466
{txt}{space 11}2015  {c |}{col 18}{res}{space 2}  .143557{col 30}{space 2} .0306107{col 41}{space 1}    4.69{col 50}{space 3}0.000{col 58}{space 4} .0835611{col 71}{space 3}  .203553
{txt}{space 11}2016  {c |}{col 18}{res}{space 2}-.2290239{col 30}{space 2} .0424158{col 41}{space 1}   -5.40{col 50}{space 3}0.000{col 58}{space 4}-.3121573{col 71}{space 3}-.1458906
{txt}{space 11}2018  {c |}{col 18}{res}{space 2} .3829816{col 30}{space 2} .0329361{col 41}{space 1}   11.63{col 50}{space 3}0.000{col 58}{space 4} .3184281{col 71}{space 3} .4475352
{txt}{space 11}2019  {c |}{col 18}{res}{space 2}-.0976156{col 30}{space 2} .0300959{col 41}{space 1}   -3.24{col 50}{space 3}0.001{col 58}{space 4}-.1566024{col 71}{space 3}-.0386288
{txt}{space 16} {c |}
{space 11}_cons {c |}{col 18}{res}{space 2} 4.464915{col 30}{space 2} .0458253{col 41}{space 1}   97.43{col 50}{space 3}0.000{col 58}{space 4} 4.375099{col 71}{space 3} 4.554731
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .81463678
         {txt}sigma_e {c |} {res} 1.2548029
             {txt}rho {c |} {res} .29650786{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est1
{txt}
{com}. 
. 
. xtreg hdd9  pdd9   $xlist  pdd9_mean $year_ETHIOPIA if country==3, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    13,511
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     5,436

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0229                                         {txt}min = {res}         1
{txt}     between = {res}0.3713                                         {txt}avg = {res}       2.5
{txt}     overall = {res}0.2595                                         {txt}max = {res}         3

                                                {txt}Wald chi2({res}21{txt})     =  {res}  3554.62
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:5,436} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .0512984{col 30}{space 2} .0105844{col 41}{space 1}    4.85{col 50}{space 3}0.000{col 58}{space 4} .0305533{col 71}{space 3} .0720434
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0476754{col 30}{space 2} .0070238{col 41}{space 1}    6.79{col 50}{space 3}0.000{col 58}{space 4}  .033909{col 71}{space 3} .0614419
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0241072{col 30}{space 2} .0538657{col 41}{space 1}   -0.45{col 50}{space 3}0.654{col 58}{space 4} -.129682{col 71}{space 3} .0814675
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0028044{col 30}{space 2} .0009433{col 41}{space 1}   -2.97{col 50}{space 3}0.003{col 58}{space 4}-.0046533{col 71}{space 3}-.0009555
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0094981{col 30}{space 2} .0330836{col 41}{space 1}   -0.29{col 50}{space 3}0.774{col 58}{space 4}-.0743408{col 71}{space 3} .0553446
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .4064271{col 30}{space 2} .0299839{col 41}{space 1}   13.55{col 50}{space 3}0.000{col 58}{space 4} .3476596{col 71}{space 3} .4651945
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}-.1383359{col 30}{space 2} .1324753{col 41}{space 1}   -1.04{col 50}{space 3}0.296{col 58}{space 4}-.3979828{col 71}{space 3} .1213109
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1920371{col 30}{space 2} .0369299{col 41}{space 1}    5.20{col 50}{space 3}0.000{col 58}{space 4} .1196558{col 71}{space 3} .2644183
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1469872{col 30}{space 2} .0451321{col 41}{space 1}    3.26{col 50}{space 3}0.001{col 58}{space 4} .0585299{col 71}{space 3} .2354444
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}-.0335136{col 30}{space 2} .0535953{col 41}{space 1}   -0.63{col 50}{space 3}0.532{col 58}{space 4}-.1385585{col 71}{space 3} .0715312
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2115585{col 30}{space 2} .0471208{col 41}{space 1}    4.49{col 50}{space 3}0.000{col 58}{space 4} .1192036{col 71}{space 3} .3039135
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1698553{col 30}{space 2}  .029409{col 41}{space 1}   -5.78{col 50}{space 3}0.000{col 58}{space 4} -.227496{col 71}{space 3}-.1122146
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0061977{col 30}{space 2} .0034661{col 41}{space 1}    1.79{col 50}{space 3}0.074{col 58}{space 4}-.0005957{col 71}{space 3} .0129912
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .2097884{col 30}{space 2} .0311529{col 41}{space 1}    6.73{col 50}{space 3}0.000{col 58}{space 4} .1487299{col 71}{space 3} .2708469
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} 1.169987{col 30}{space 2} .2161981{col 41}{space 1}    5.41{col 50}{space 3}0.000{col 58}{space 4} .7462466{col 71}{space 3} 1.593727
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .5327733{col 30}{space 2} .0561351{col 41}{space 1}    9.49{col 50}{space 3}0.000{col 58}{space 4} .4227504{col 71}{space 3} .6427961
{txt}electricity_mean {c |}{col 18}{res}{space 2} .6664552{col 30}{space 2} .0671361{col 41}{space 1}    9.93{col 50}{space 3}0.000{col 58}{space 4} .5348708{col 71}{space 3} .7980395
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .5003858{col 30}{space 2} .0814643{col 41}{space 1}    6.14{col 50}{space 3}0.000{col 58}{space 4} .3407187{col 71}{space 3} .6600529
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .0848497{col 30}{space 2} .0598687{col 41}{space 1}    1.42{col 50}{space 3}0.156{col 58}{space 4}-.0324908{col 71}{space 3} .2021902
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .0039661{col 30}{space 2} .0142828{col 41}{space 1}    0.28{col 50}{space 3}0.781{col 58}{space 4}-.0240277{col 71}{space 3} .0319599
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}-.1924394{col 30}{space 2} .0211475{col 41}{space 1}   -9.10{col 50}{space 3}0.000{col 58}{space 4}-.2338878{col 71}{space 3} -.150991
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 3.169398{col 30}{space 2}  .068152{col 41}{space 1}   46.50{col 50}{space 3}0.000{col 58}{space 4} 3.035822{col 71}{space 3} 3.302973
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .76124145
         {txt}sigma_e {c |} {res} 1.1126502
             {txt}rho {c |} {res} .31884193{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est2
{txt}
{com}. 
. xtreg hdd9  pdd9   $xlist  pdd9_mean $year_MALAWI if country==6, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     9,163
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     3,447

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0401                                         {txt}min = {res}         1
{txt}     between = {res}0.3706                                         {txt}avg = {res}       2.7
{txt}     overall = {res}0.2936                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}22{txt})     =  {res}  3127.04
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,447} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .1160662{col 30}{space 2}  .014321{col 41}{space 1}    8.10{col 50}{space 3}0.000{col 58}{space 4} .0879976{col 71}{space 3} .1441349
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0117709{col 30}{space 2} .0087768{col 41}{space 1}   -1.34{col 50}{space 3}0.180{col 58}{space 4}-.0289731{col 71}{space 3} .0054313
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.3383894{col 30}{space 2} .0733556{col 41}{space 1}   -4.61{col 50}{space 3}0.000{col 58}{space 4}-.4821638{col 71}{space 3} -.194615
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0031304{col 30}{space 2} .0012647{col 41}{space 1}   -2.48{col 50}{space 3}0.013{col 58}{space 4}-.0056092{col 71}{space 3}-.0006516
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0999807{col 30}{space 2} .0419376{col 41}{space 1}   -2.38{col 50}{space 3}0.017{col 58}{space 4}-.1821768{col 71}{space 3}-.0177845
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2929747{col 30}{space 2} .0447797{col 41}{space 1}    6.54{col 50}{space 3}0.000{col 58}{space 4} .2052081{col 71}{space 3} .3807413
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2489785{col 30}{space 2}  .136827{col 41}{space 1}    1.82{col 50}{space 3}0.069{col 58}{space 4}-.0191975{col 71}{space 3} .5171544
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2573716{col 30}{space 2} .0528726{col 41}{space 1}    4.87{col 50}{space 3}0.000{col 58}{space 4} .1537432{col 71}{space 3}     .361
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .4530508{col 30}{space 2} .0857548{col 41}{space 1}    5.28{col 50}{space 3}0.000{col 58}{space 4} .2849744{col 71}{space 3} .6211272
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1757857{col 30}{space 2}  .056304{col 41}{space 1}    3.12{col 50}{space 3}0.002{col 58}{space 4} .0654319{col 71}{space 3} .2861394
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2602988{col 30}{space 2} .0413476{col 41}{space 1}    6.30{col 50}{space 3}0.000{col 58}{space 4} .1792591{col 71}{space 3} .3413386
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1950077{col 30}{space 2} .0327526{col 41}{space 1}   -5.95{col 50}{space 3}0.000{col 58}{space 4}-.2592016{col 71}{space 3}-.1308138
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0228484{col 30}{space 2} .0262653{col 41}{space 1}    0.87{col 50}{space 3}0.384{col 58}{space 4}-.0286307{col 71}{space 3} .0743275
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0309318{col 30}{space 2} .0473574{col 41}{space 1}    0.65{col 50}{space 3}0.514{col 58}{space 4}-.0618871{col 71}{space 3} .1237506
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .3134129{col 30}{space 2}  .212582{col 41}{space 1}    1.47{col 50}{space 3}0.140{col 58}{space 4}-.1032402{col 71}{space 3}  .730066
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .4575541{col 30}{space 2} .0763532{col 41}{space 1}    5.99{col 50}{space 3}0.000{col 58}{space 4} .3079046{col 71}{space 3} .6072035
{txt}electricity_mean {c |}{col 18}{res}{space 2} .7258006{col 30}{space 2} .1103959{col 41}{space 1}    6.57{col 50}{space 3}0.000{col 58}{space 4} .5094286{col 71}{space 3} .9421725
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .3856524{col 30}{space 2} .0789567{col 41}{space 1}    4.88{col 50}{space 3}0.000{col 58}{space 4} .2309001{col 71}{space 3} .5404047
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .3399225{col 30}{space 2} .0675471{col 41}{space 1}    5.03{col 50}{space 3}0.000{col 58}{space 4} .2075325{col 71}{space 3} .4723124
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.0780017{col 30}{space 2} .0206163{col 41}{space 1}   -3.78{col 50}{space 3}0.000{col 58}{space 4}-.1184089{col 71}{space 3}-.0375944
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}  .116201{col 30}{space 2} .0419337{col 41}{space 1}    2.77{col 50}{space 3}0.006{col 58}{space 4} .0340125{col 71}{space 3} .1983895
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .0837529{col 30}{space 2} .0350109{col 41}{space 1}    2.39{col 50}{space 3}0.017{col 58}{space 4} .0151328{col 71}{space 3}  .152373
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 5.318584{col 30}{space 2} .0879862{col 41}{space 1}   60.45{col 50}{space 3}0.000{col 58}{space 4} 5.146134{col 71}{space 3} 5.491034
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .69413719
         {txt}sigma_e {c |} {res} 1.3063515
             {txt}rho {c |} {res} .22017486{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est3
{txt}
{com}. 
. 
. xtreg hdd9  pdd9   $xlist  pdd9_mean $year_NIGER if country==1, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     7,046
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     4,069

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0394                                         {txt}min = {res}         1
{txt}     between = {res}0.2380                                         {txt}avg = {res}       1.7
{txt}     overall = {res}0.1908                                         {txt}max = {res}         2

                                                {txt}Wald chi2({res}21{txt})     =  {res}  1600.06
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:4,069} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .2448114{col 30}{space 2} .0346647{col 41}{space 1}    7.06{col 50}{space 3}0.000{col 58}{space 4} .1768697{col 71}{space 3}  .312753
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0138424{col 30}{space 2} .0064218{col 41}{space 1}    2.16{col 50}{space 3}0.031{col 58}{space 4} .0012558{col 71}{space 3} .0264289
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0341181{col 30}{space 2} .0962046{col 41}{space 1}   -0.35{col 50}{space 3}0.723{col 58}{space 4}-.2226757{col 71}{space 3} .1544396
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0028576{col 30}{space 2} .0013875{col 41}{space 1}    2.06{col 50}{space 3}0.039{col 58}{space 4} .0001383{col 71}{space 3}  .005577
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .1124151{col 30}{space 2} .0575238{col 41}{space 1}    1.95{col 50}{space 3}0.051{col 58}{space 4}-.0003294{col 71}{space 3} .2251595
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3465292{col 30}{space 2} .0440123{col 41}{space 1}    7.87{col 50}{space 3}0.000{col 58}{space 4} .2602667{col 71}{space 3} .4327917
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2422793{col 30}{space 2} .0962715{col 41}{space 1}    2.52{col 50}{space 3}0.012{col 58}{space 4} .0535907{col 71}{space 3} .4309679
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0983312{col 30}{space 2} .0746049{col 41}{space 1}    1.32{col 50}{space 3}0.187{col 58}{space 4}-.0478916{col 71}{space 3} .2445541
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .2310626{col 30}{space 2} .1059337{col 41}{space 1}    2.18{col 50}{space 3}0.029{col 58}{space 4} .0234363{col 71}{space 3} .4386888
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2207883{col 30}{space 2} .0839148{col 41}{space 1}    2.63{col 50}{space 3}0.009{col 58}{space 4} .0563182{col 71}{space 3} .3852583
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}-.1783366{col 30}{space 2} .0655485{col 41}{space 1}   -2.72{col 50}{space 3}0.007{col 58}{space 4}-.3068093{col 71}{space 3} -.049864
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}  -.12748{col 30}{space 2} .0452289{col 41}{space 1}   -2.82{col 50}{space 3}0.005{col 58}{space 4}-.2161269{col 71}{space 3} -.038833
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0012235{col 30}{space 2} .0015834{col 41}{space 1}   -0.77{col 50}{space 3}0.440{col 58}{space 4} -.004327{col 71}{space 3}   .00188
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .2034678{col 30}{space 2} .2171383{col 41}{space 1}    0.94{col 50}{space 3}0.349{col 58}{space 4}-.2221155{col 71}{space 3}  .629051
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1101917{col 30}{space 2} .1187419{col 41}{space 1}    0.93{col 50}{space 3}0.353{col 58}{space 4}-.1225382{col 71}{space 3} .3429216
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}   .33457{col 30}{space 2} .0919073{col 41}{space 1}    3.64{col 50}{space 3}0.000{col 58}{space 4}  .154435{col 71}{space 3}  .514705
{txt}electricity_mean {c |}{col 18}{res}{space 2} .5092648{col 30}{space 2} .1241275{col 41}{space 1}    4.10{col 50}{space 3}0.000{col 58}{space 4} .2659795{col 71}{space 3} .7525502
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1855409{col 30}{space 2} .1037084{col 41}{space 1}    1.79{col 50}{space 3}0.074{col 58}{space 4}-.0177238{col 71}{space 3} .3888056
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .4429435{col 30}{space 2} .0810433{col 41}{space 1}    5.47{col 50}{space 3}0.000{col 58}{space 4} .2841016{col 71}{space 3} .6017854
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.2722478{col 30}{space 2}  .039394{col 41}{space 1}   -6.91{col 50}{space 3}0.000{col 58}{space 4}-.3494587{col 71}{space 3}-.1950369
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2} .2577575{col 30}{space 2} .0363371{col 41}{space 1}    7.09{col 50}{space 3}0.000{col 58}{space 4} .1865381{col 71}{space 3} .3289769
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}   4.5585{col 30}{space 2}  .107879{col 41}{space 1}   42.26{col 50}{space 3}0.000{col 58}{space 4} 4.347061{col 71}{space 3} 4.769939
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .61793953
         {txt}sigma_e {c |} {res} 1.3703359
             {txt}rho {c |} {res} .16898455{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est4
{txt}
{com}. 
. 
. xtreg hdd9  pdd9   $xlist  pdd9_mean $year_NIGERIA if country==2, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    18,592
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     8,222

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0392                                         {txt}min = {res}         1
{txt}     between = {res}0.3100                                         {txt}avg = {res}       2.3
{txt}     overall = {res}0.2618                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}23{txt})     =  {res}  4916.63
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:8,222} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .0954555{col 30}{space 2} .0142286{col 41}{space 1}    6.71{col 50}{space 3}0.000{col 58}{space 4}  .067568{col 71}{space 3} .1233431
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0251421{col 30}{space 2} .0044371{col 41}{space 1}   -5.67{col 50}{space 3}0.000{col 58}{space 4}-.0338386{col 71}{space 3}-.0164456
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .1374149{col 30}{space 2} .0489552{col 41}{space 1}    2.81{col 50}{space 3}0.005{col 58}{space 4} .0414646{col 71}{space 3} .2333653
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0045327{col 30}{space 2} .0009018{col 41}{space 1}    5.03{col 50}{space 3}0.000{col 58}{space 4} .0027652{col 71}{space 3} .0063002
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .2208006{col 30}{space 2} .0350994{col 41}{space 1}    6.29{col 50}{space 3}0.000{col 58}{space 4} .1520071{col 71}{space 3} .2895942
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .1965188{col 30}{space 2} .0272426{col 41}{space 1}    7.21{col 50}{space 3}0.000{col 58}{space 4} .1431244{col 71}{space 3} .2499132
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0383009{col 30}{space 2} .0383457{col 41}{space 1}    1.00{col 50}{space 3}0.318{col 58}{space 4}-.0368553{col 71}{space 3}  .113457
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1851155{col 30}{space 2} .0383103{col 41}{space 1}    4.83{col 50}{space 3}0.000{col 58}{space 4} .1100287{col 71}{space 3} .2602023
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0875706{col 30}{space 2}  .044639{col 41}{space 1}    1.96{col 50}{space 3}0.050{col 58}{space 4} .0000796{col 71}{space 3} .1750615
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2121287{col 30}{space 2} .0480928{col 41}{space 1}    4.41{col 50}{space 3}0.000{col 58}{space 4} .1178685{col 71}{space 3}  .306389
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2779439{col 30}{space 2} .0389845{col 41}{space 1}    7.13{col 50}{space 3}0.000{col 58}{space 4} .2015356{col 71}{space 3} .3543521
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0071558{col 30}{space 2} .0466389{col 41}{space 1}   -0.15{col 50}{space 3}0.878{col 58}{space 4}-.0985664{col 71}{space 3} .0842548
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0099185{col 30}{space 2} .0068981{col 41}{space 1}   -1.44{col 50}{space 3}0.150{col 58}{space 4}-.0234386{col 71}{space 3} .0036016
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}  .322513{col 30}{space 2} .0598252{col 41}{space 1}    5.39{col 50}{space 3}0.000{col 58}{space 4} .2052577{col 71}{space 3} .4397683
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}-.0593143{col 30}{space 2}  .053329{col 41}{space 1}   -1.11{col 50}{space 3}0.266{col 58}{space 4}-.1638371{col 71}{space 3} .0452086
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .8210809{col 30}{space 2} .0585002{col 41}{space 1}   14.04{col 50}{space 3}0.000{col 58}{space 4} .7064227{col 71}{space 3} .9357391
{txt}electricity_mean {c |}{col 18}{res}{space 2} .8517745{col 30}{space 2} .0574237{col 41}{space 1}   14.83{col 50}{space 3}0.000{col 58}{space 4} .7392261{col 71}{space 3} .9643228
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .2504516{col 30}{space 2}  .063917{col 41}{space 1}    3.92{col 50}{space 3}0.000{col 58}{space 4} .1251765{col 71}{space 3} .3757267
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.0103826{col 30}{space 2} .0511221{col 41}{space 1}   -0.20{col 50}{space 3}0.839{col 58}{space 4}-.1105801{col 71}{space 3} .0898149
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.0772695{col 30}{space 2} .0182096{col 41}{space 1}   -4.24{col 50}{space 3}0.000{col 58}{space 4}-.1129598{col 71}{space 3}-.0415793
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.5884686{col 30}{space 2} .0307655{col 41}{space 1}  -19.13{col 50}{space 3}0.000{col 58}{space 4}-.6487679{col 71}{space 3}-.5281693
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2}-.4917889{col 30}{space 2}  .031016{col 41}{space 1}  -15.86{col 50}{space 3}0.000{col 58}{space 4}-.5525792{col 71}{space 3}-.4309987
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2}-.3387276{col 30}{space 2} .0305652{col 41}{space 1}  -11.08{col 50}{space 3}0.000{col 58}{space 4}-.3986343{col 71}{space 3}-.2788209
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.524212{col 30}{space 2} .0744022{col 41}{space 1}   60.81{col 50}{space 3}0.000{col 58}{space 4} 4.378386{col 71}{space 3} 4.670037
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .85893868
         {txt}sigma_e {c |} {res} 1.2348383
             {txt}rho {c |} {res} .32607409{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est5
{txt}
{com}. 
. 
. xtreg hdd9  pdd9   $xlist  pdd9_mean $year_TANZANIA if country==5, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    21,117
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}    10,363

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0310                                         {txt}min = {res}         1
{txt}     between = {res}0.2176                                         {txt}avg = {res}       2.0
{txt}     overall = {res}0.1877                                         {txt}max = {res}         5

                                                {txt}Wald chi2({res}23{txt})     =  {res}  3822.97
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:10,363} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .1439935{col 30}{space 2} .0108076{col 41}{space 1}   13.32{col 50}{space 3}0.000{col 58}{space 4} .1228109{col 71}{space 3} .1651761
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0044703{col 30}{space 2} .0042332{col 41}{space 1}   -1.06{col 50}{space 3}0.291{col 58}{space 4}-.0127672{col 71}{space 3} .0038267
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0888128{col 30}{space 2} .0507284{col 41}{space 1}    1.75{col 50}{space 3}0.080{col 58}{space 4}-.0106129{col 71}{space 3} .1882386
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0008937{col 30}{space 2} .0008185{col 41}{space 1}   -1.09{col 50}{space 3}0.275{col 58}{space 4} -.002498{col 71}{space 3} .0007105
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0700597{col 30}{space 2} .0276496{col 41}{space 1}    2.53{col 50}{space 3}0.011{col 58}{space 4} .0158676{col 71}{space 3} .1242518
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3105817{col 30}{space 2} .0286183{col 41}{space 1}   10.85{col 50}{space 3}0.000{col 58}{space 4} .2544909{col 71}{space 3} .3666725
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1684405{col 30}{space 2} .0590209{col 41}{space 1}    2.85{col 50}{space 3}0.004{col 58}{space 4} .0527616{col 71}{space 3} .2841193
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .3013008{col 30}{space 2} .0395684{col 41}{space 1}    7.61{col 50}{space 3}0.000{col 58}{space 4} .2237481{col 71}{space 3} .3788534
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0785698{col 30}{space 2} .0425272{col 41}{space 1}    1.85{col 50}{space 3}0.065{col 58}{space 4} -.004782{col 71}{space 3} .1619217
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1313993{col 30}{space 2} .0298078{col 41}{space 1}    4.41{col 50}{space 3}0.000{col 58}{space 4} .0729771{col 71}{space 3} .1898215
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}  .257655{col 30}{space 2} .0315578{col 41}{space 1}    8.16{col 50}{space 3}0.000{col 58}{space 4} .1958028{col 71}{space 3} .3195073
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1510342{col 30}{space 2} .0265906{col 41}{space 1}   -5.68{col 50}{space 3}0.000{col 58}{space 4}-.2031508{col 71}{space 3}-.0989176
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0021208{col 30}{space 2} .0019355{col 41}{space 1}    1.10{col 50}{space 3}0.273{col 58}{space 4}-.0016726{col 71}{space 3} .0059142
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0101063{col 30}{space 2} .0282273{col 41}{space 1}    0.36{col 50}{space 3}0.720{col 58}{space 4}-.0452182{col 71}{space 3} .0654308
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .5031243{col 30}{space 2} .0760903{col 41}{space 1}    6.61{col 50}{space 3}0.000{col 58}{space 4} .3539901{col 71}{space 3} .6522586
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .4077521{col 30}{space 2} .0538653{col 41}{space 1}    7.57{col 50}{space 3}0.000{col 58}{space 4} .3021781{col 71}{space 3} .5133261
{txt}electricity_mean {c |}{col 18}{res}{space 2} .5488096{col 30}{space 2} .0548292{col 41}{space 1}   10.01{col 50}{space 3}0.000{col 58}{space 4} .4413464{col 71}{space 3} .6562728
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1183783{col 30}{space 2} .0424295{col 41}{space 1}    2.79{col 50}{space 3}0.005{col 58}{space 4}  .035218{col 71}{space 3} .2015386
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .2360312{col 30}{space 2} .0434985{col 41}{space 1}    5.43{col 50}{space 3}0.000{col 58}{space 4} .1507757{col 71}{space 3} .3212867
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.1016559{col 30}{space 2} .0130001{col 41}{space 1}   -7.82{col 50}{space 3}0.000{col 58}{space 4}-.1271357{col 71}{space 3}-.0761762
{txt}{space 10}year_1 {c |}{col 18}{res}{space 2} .0775034{col 30}{space 2} .0289879{col 41}{space 1}    2.67{col 50}{space 3}0.008{col 58}{space 4} .0206881{col 71}{space 3} .1343187
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2} .0950504{col 30}{space 2} .0242958{col 41}{space 1}    3.91{col 50}{space 3}0.000{col 58}{space 4} .0474315{col 71}{space 3} .1426692
{txt}{space 10}year_7 {c |}{col 18}{res}{space 2} .1098999{col 30}{space 2} .0270916{col 41}{space 1}    4.06{col 50}{space 3}0.000{col 58}{space 4} .0568015{col 71}{space 3} .1629984
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.368412{col 30}{space 2}  .063433{col 41}{space 1}   68.87{col 50}{space 3}0.000{col 58}{space 4} 4.244085{col 71}{space 3} 4.492738
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .79869839
         {txt}sigma_e {c |} {res} 1.2448832
             {txt}rho {c |} {res} .29159972{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est6
{txt}
{com}. 
. xtreg hdd9  pdd9   $xlist  pdd9_mean  $year_UGANDA if country==4, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    20,313
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     5,107

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0480                                         {txt}min = {res}         1
{txt}     between = {res}0.2727                                         {txt}avg = {res}       4.0
{txt}     overall = {res}0.1889                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}25{txt})     =  {res}  2986.99
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:5,107} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2}   .09694{col 30}{space 2} .0099922{col 41}{space 1}    9.70{col 50}{space 3}0.000{col 58}{space 4} .0773555{col 71}{space 3} .1165244
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0151554{col 30}{space 2} .0051749{col 41}{space 1}    2.93{col 50}{space 3}0.003{col 58}{space 4} .0050128{col 71}{space 3} .0252979
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .1504517{col 30}{space 2} .0552696{col 41}{space 1}    2.72{col 50}{space 3}0.006{col 58}{space 4} .0421252{col 71}{space 3} .2587781
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0015235{col 30}{space 2} .0009812{col 41}{space 1}   -1.55{col 50}{space 3}0.121{col 58}{space 4}-.0034467{col 71}{space 3} .0003997
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0672678{col 30}{space 2} .0317513{col 41}{space 1}    2.12{col 50}{space 3}0.034{col 58}{space 4} .0050365{col 71}{space 3} .1294991
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2662947{col 30}{space 2} .0313285{col 41}{space 1}    8.50{col 50}{space 3}0.000{col 58}{space 4}  .204892{col 71}{space 3} .3276975
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2268061{col 30}{space 2} .0499062{col 41}{space 1}    4.54{col 50}{space 3}0.000{col 58}{space 4} .1289917{col 71}{space 3} .3246204
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2537338{col 30}{space 2} .0338444{col 41}{space 1}    7.50{col 50}{space 3}0.000{col 58}{space 4}    .1874{col 71}{space 3} .3200675
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .3387038{col 30}{space 2} .0340837{col 41}{space 1}    9.94{col 50}{space 3}0.000{col 58}{space 4}  .271901{col 71}{space 3} .4055065
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}  .061065{col 30}{space 2} .0276843{col 41}{space 1}    2.21{col 50}{space 3}0.027{col 58}{space 4} .0068048{col 71}{space 3} .1153253
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .1937012{col 30}{space 2} .0283854{col 41}{space 1}    6.82{col 50}{space 3}0.000{col 58}{space 4} .1380668{col 71}{space 3} .2493355
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0151502{col 30}{space 2} .0235394{col 41}{space 1}   -0.64{col 50}{space 3}0.520{col 58}{space 4}-.0612866{col 71}{space 3} .0309861
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0013121{col 30}{space 2} .0011844{col 41}{space 1}    1.11{col 50}{space 3}0.268{col 58}{space 4}-.0010094{col 71}{space 3} .0036335
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.0072006{col 30}{space 2} .0266275{col 41}{space 1}   -0.27{col 50}{space 3}0.787{col 58}{space 4}-.0593896{col 71}{space 3} .0449884
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .2215519{col 30}{space 2} .0800534{col 41}{space 1}    2.77{col 50}{space 3}0.006{col 58}{space 4} .0646501{col 71}{space 3} .3784537
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .3981731{col 30}{space 2}  .059736{col 41}{space 1}    6.67{col 50}{space 3}0.000{col 58}{space 4} .2810926{col 71}{space 3} .5152536
{txt}electricity_mean {c |}{col 18}{res}{space 2} .4967286{col 30}{space 2} .0640024{col 41}{space 1}    7.76{col 50}{space 3}0.000{col 58}{space 4} .3712863{col 71}{space 3}  .622171
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1516256{col 30}{space 2} .0529747{col 41}{space 1}    2.86{col 50}{space 3}0.004{col 58}{space 4}  .047797{col 71}{space 3} .2554541
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .3567216{col 30}{space 2} .0511623{col 41}{space 1}    6.97{col 50}{space 3}0.000{col 58}{space 4} .2564454{col 71}{space 3} .4569978
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.0070907{col 30}{space 2} .0149307{col 41}{space 1}   -0.47{col 50}{space 3}0.635{col 58}{space 4}-.0363543{col 71}{space 3} .0221729
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.1668303{col 30}{space 2} .0323825{col 41}{space 1}   -5.15{col 50}{space 3}0.000{col 58}{space 4}-.2302988{col 71}{space 3}-.1033617
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2}-.0543754{col 30}{space 2} .0304832{col 41}{space 1}   -1.78{col 50}{space 3}0.074{col 58}{space 4}-.1141213{col 71}{space 3} .0053705
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .3287094{col 30}{space 2} .0308382{col 41}{space 1}   10.66{col 50}{space 3}0.000{col 58}{space 4} .2682676{col 71}{space 3} .3891513
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2} .0733056{col 30}{space 2} .0306156{col 41}{space 1}    2.39{col 50}{space 3}0.017{col 58}{space 4} .0133001{col 71}{space 3} .1333111
{txt}{space 9}year_10 {c |}{col 18}{res}{space 2} .2759902{col 30}{space 2}  .029117{col 41}{space 1}    9.48{col 50}{space 3}0.000{col 58}{space 4} .2189219{col 71}{space 3} .3330585
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 3.963684{col 30}{space 2} .0822749{col 41}{space 1}   48.18{col 50}{space 3}0.000{col 58}{space 4} 3.802428{col 71}{space 3}  4.12494
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res}  .8641309
         {txt}sigma_e {c |} {res} 1.2834766
             {txt}rho {c |} {res} .31190954{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est7
{txt}
{com}. esttab using  S2.rtf, se replace star(* 0.1 ** 0.05 *** 0.01) cells (b(star fmt(%9.3f)) se (par(( )) fmt(%9.3f)))  stats(N r2_b  r2_w r2_o p, fmt(%4.0f %4.3f %4.3f %6.3f)) keep(pdd9   $xlist  pdd9_mean _cons)
{res}{txt}(note: file S2.rtf not found)
(output written to {browse  `"S2.rtf"'})

{com}. 
. 
. 
. 
. ********************************************************************************
. *                             Table S3                                         *
. ********************************************************************************
. preserve
{txt}
{com}. drop if dist_popcenter==.
{txt}(27,826 observations deleted)

{com}. 
. drop pdd9_mean  no_species_mean hhsize_mean dependent_share_mean head_age_mean female_head_mean head_read_mean motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean weather_shock_mean plot_area_mean other_crop_mean
{txt}
{com}. egen pdd9_mean=mean(pdd9), by(HHID_panel)
{txt}
{com}. egen pdd9_mean_vill=mean(pdd9_vill), by(HHID_panel)
{txt}(887 missing values generated)

{com}. egen pdd9_mean_town=mean(pdd9_town), by(HHID_panel)
{txt}(839 missing values generated)

{com}. egen pdd9_mean_dist=mean(pdd9_dist), by(HHID_panel)
{txt}(837 missing values generated)

{com}. 
. foreach x of varlist hhsize dependent_share head_age female_head head_read  motobike phone  electricity wagejob enterprise weather_shock  plot_area other_crop{c -(}
{txt}  2{com}. egen `x'_mean=mean(`x'), by(HHID_panel)
{txt}  3{com}. {c )-}
{txt}
{com}. 
. 
. eststo clear
{txt}
{com}. xtreg hdd9  c.pdd9##c.dist_popcenter   $xlist  pdd9_mean  i.country i.year  , cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    61,916
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}    27,794

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0272                                         {txt}min = {res}         1
{txt}     between = {res}0.3860                                         {txt}avg = {res}       2.2
{txt}     overall = {res}0.3180                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}35{txt})     =  {res} 22660.51
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 89:(Std. Err. adjusted for {res:27,794} clusters in HHID_panel)}
{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 25}{c |}{col 37}    Robust
{col 1}                   hdd9{col 25}{c |}      Coef.{col 37}   Std. Err.{col 49}      z{col 57}   P>|z|{col 65}     [95% Con{col 78}f. Interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 19}pdd9 {c |}{col 25}{res}{space 2} .0606134{col 37}{space 2} .0075023{col 48}{space 1}    8.08{col 57}{space 3}0.000{col 65}{space 4} .0459092{col 78}{space 3} .0753176
{txt}{space 9}dist_popcenter {c |}{col 25}{res}{space 2}-.0047496{col 37}{space 2} .0003483{col 48}{space 1}  -13.64{col 57}{space 3}0.000{col 65}{space 4}-.0054322{col 78}{space 3} -.004067
{txt}{space 23} {c |}
c.pdd9#c.dist_popcenter {c |}{col 25}{res}{space 2} .0007449{col 37}{space 2} .0001069{col 48}{space 1}    6.97{col 57}{space 3}0.000{col 65}{space 4} .0005354{col 78}{space 3} .0009543
{txt}{space 23} {c |}
{space 17}hhsize {c |}{col 25}{res}{space 2}-.0025116{col 37}{space 2} .0025756{col 48}{space 1}   -0.98{col 57}{space 3}0.329{col 65}{space 4}-.0075597{col 78}{space 3} .0025366
{txt}{space 8}dependent_share {c |}{col 25}{res}{space 2} .0751468{col 37}{space 2} .0286456{col 48}{space 1}    2.62{col 57}{space 3}0.009{col 65}{space 4} .0190025{col 78}{space 3} .1312912
{txt}{space 15}head_age {c |}{col 25}{res}{space 2}-.0001677{col 37}{space 2} .0004776{col 48}{space 1}   -0.35{col 57}{space 3}0.725{col 65}{space 4}-.0011037{col 78}{space 3} .0007683
{txt}{space 12}female_head {c |}{col 25}{res}{space 2}  .039663{col 37}{space 2} .0172499{col 48}{space 1}    2.30{col 57}{space 3}0.021{col 65}{space 4} .0058539{col 78}{space 3} .0734722
{txt}{space 14}head_read {c |}{col 25}{res}{space 2}  .288375{col 37}{space 2}  .015346{col 48}{space 1}   18.79{col 57}{space 3}0.000{col 65}{space 4} .2582975{col 78}{space 3} .3184526
{txt}{space 15}motobike {c |}{col 25}{res}{space 2} .0660562{col 37}{space 2} .0300213{col 48}{space 1}    2.20{col 57}{space 3}0.028{col 65}{space 4} .0072156{col 78}{space 3} .1248969
{txt}{space 18}phone {c |}{col 25}{res}{space 2} .1731451{col 37}{space 2} .0206509{col 48}{space 1}    8.38{col 57}{space 3}0.000{col 65}{space 4} .1326701{col 78}{space 3} .2136201
{txt}{space 12}electricity {c |}{col 25}{res}{space 2} .1021967{col 37}{space 2} .0276826{col 48}{space 1}    3.69{col 57}{space 3}0.000{col 65}{space 4} .0479398{col 78}{space 3} .1564536
{txt}{space 16}wagejob {c |}{col 25}{res}{space 2} .1056096{col 37}{space 2} .0218033{col 48}{space 1}    4.84{col 57}{space 3}0.000{col 65}{space 4} .0628759{col 78}{space 3} .1483432
{txt}{space 13}enterprise {c |}{col 25}{res}{space 2} .1894007{col 37}{space 2} .0203067{col 48}{space 1}    9.33{col 57}{space 3}0.000{col 65}{space 4} .1496004{col 78}{space 3}  .229201
{txt}{space 10}weather_shock {c |}{col 25}{res}{space 2} -.054551{col 37}{space 2} .0163137{col 48}{space 1}   -3.34{col 57}{space 3}0.001{col 65}{space 4}-.0865252{col 78}{space 3}-.0225768
{txt}{space 14}plot_area {c |}{col 25}{res}{space 2} .0007793{col 37}{space 2} .0010059{col 48}{space 1}    0.77{col 57}{space 3}0.439{col 65}{space 4}-.0011923{col 78}{space 3} .0027509
{txt}{space 13}other_crop {c |}{col 25}{res}{space 2} .1182518{col 37}{space 2}  .018633{col 48}{space 1}    6.35{col 57}{space 3}0.000{col 65}{space 4} .0817318{col 78}{space 3} .1547718
{txt}{space 10}motobike_mean {c |}{col 25}{res}{space 2} .0192306{col 37}{space 2} .0402244{col 48}{space 1}    0.48{col 57}{space 3}0.633{col 65}{space 4}-.0596077{col 78}{space 3} .0980688
{txt}{space 13}phone_mean {c |}{col 25}{res}{space 2} .6178905{col 37}{space 2} .0293936{col 48}{space 1}   21.02{col 57}{space 3}0.000{col 65}{space 4} .5602802{col 78}{space 3} .6755008
{txt}{space 7}electricity_mean {c |}{col 25}{res}{space 2} .7747215{col 37}{space 2} .0355541{col 48}{space 1}   21.79{col 57}{space 3}0.000{col 65}{space 4} .7050367{col 78}{space 3} .8444063
{txt}{space 11}wagejob_mean {c |}{col 25}{res}{space 2} .2159278{col 37}{space 2} .0308455{col 48}{space 1}    7.00{col 57}{space 3}0.000{col 65}{space 4} .1554718{col 78}{space 3} .2763838
{txt}{space 8}enterprise_mean {c |}{col 25}{res}{space 2} .1363805{col 37}{space 2} .0270287{col 48}{space 1}    5.05{col 57}{space 3}0.000{col 65}{space 4} .0834052{col 78}{space 3} .1893558
{txt}{space 14}pdd9_mean {c |}{col 25}{res}{space 2}-.0253731{col 37}{space 2} .0083682{col 48}{space 1}   -3.03{col 57}{space 3}0.002{col 65}{space 4}-.0417744{col 78}{space 3}-.0089718
{txt}{space 23} {c |}
{space 16}country {c |}
{space 15}Nigeria  {c |}{col 25}{res}{space 2}-.4562276{col 37}{space 2} .0365981{col 48}{space 1}  -12.47{col 57}{space 3}0.000{col 65}{space 4}-.5279586{col 78}{space 3}-.3844966
{txt}{space 14}Ethiopia  {c |}{col 25}{res}{space 2}-1.493603{col 37}{space 2}   .03346{col 48}{space 1}  -44.64{col 57}{space 3}0.000{col 65}{space 4}-1.559183{col 78}{space 3}-1.428022
{txt}{space 16}Uganda  {c |}{col 25}{res}{space 2}  -.58739{col 37}{space 2}  .037155{col 48}{space 1}  -15.81{col 57}{space 3}0.000{col 65}{space 4}-.6602125{col 78}{space 3}-.5145675
{txt}{space 14}Tanzania  {c |}{col 25}{res}{space 2} -.101613{col 37}{space 2}  .039484{col 48}{space 1}   -2.57{col 57}{space 3}0.010{col 65}{space 4}-.1790002{col 78}{space 3}-.0242258
{txt}{space 16}Malawi  {c |}{col 25}{res}{space 2} .5701751{col 37}{space 2} .0424669{col 48}{space 1}   13.43{col 57}{space 3}0.000{col 65}{space 4} .4869414{col 78}{space 3} .6534088
{txt}{space 23} {c |}
{space 19}year {c |}
{space 18}2009  {c |}{col 25}{res}{space 2} .0377544{col 37}{space 2} .0427301{col 48}{space 1}    0.88{col 57}{space 3}0.377{col 65}{space 4}-.0459951{col 78}{space 3} .1215038
{txt}{space 18}2010  {c |}{col 25}{res}{space 2} .0671174{col 37}{space 2} .0295148{col 48}{space 1}    2.27{col 57}{space 3}0.023{col 65}{space 4} .0092694{col 78}{space 3} .1249653
{txt}{space 18}2011  {c |}{col 25}{res}{space 2} .1782924{col 37}{space 2} .0370694{col 48}{space 1}    4.81{col 57}{space 3}0.000{col 65}{space 4} .1056377{col 78}{space 3} .2509471
{txt}{space 18}2012  {c |}{col 25}{res}{space 2} .0822339{col 37}{space 2}  .029415{col 48}{space 1}    2.80{col 57}{space 3}0.005{col 65}{space 4} .0245816{col 78}{space 3} .1398862
{txt}{space 18}2013  {c |}{col 25}{res}{space 2}  .054531{col 37}{space 2}  .037428{col 48}{space 1}    1.46{col 57}{space 3}0.145{col 65}{space 4}-.0188265{col 78}{space 3} .1278884
{txt}{space 18}2014  {c |}{col 25}{res}{space 2}-.0790933{col 37}{space 2} .0509241{col 48}{space 1}   -1.55{col 57}{space 3}0.120{col 65}{space 4}-.1789027{col 78}{space 3}  .020716
{txt}{space 18}2015  {c |}{col 25}{res}{space 2} .3193888{col 37}{space 2} .0345679{col 48}{space 1}    9.24{col 57}{space 3}0.000{col 65}{space 4} .2516369{col 78}{space 3} .3871407
{txt}{space 18}2018  {c |}{col 25}{res}{space 2} .6456693{col 37}{space 2} .0394445{col 48}{space 1}   16.37{col 57}{space 3}0.000{col 65}{space 4} .5683595{col 78}{space 3}  .722979
{txt}{space 23} {c |}
{space 18}_cons {c |}{col 25}{res}{space 2} 4.646407{col 37}{space 2} .0572371{col 48}{space 1}   81.18{col 57}{space 3}0.000{col 65}{space 4} 4.534224{col 78}{space 3} 4.758589
{txt}{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                sigma_u {c |} {res} .83526647
                {txt}sigma_e {c |} {res} 1.2184054
                    {txt}rho {c |} {res} .31971218{txt}   (fraction of variance due to u_i)
{hline 24}{c BT}{hline 64}

{com}. eststo est1
{txt}
{com}. 
. 
. xtreg hdd9  c.pdd9##c.dist_popcenter   $xlist  pdd9_mean  year_6 if country==3, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    13,494
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     5,431

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0222                                         {txt}min = {res}         1
{txt}     between = {res}0.3773                                         {txt}avg = {res}       2.5
{txt}     overall = {res}0.2636                                         {txt}max = {res}         3

                                                {txt}Wald chi2({res}23{txt})     =  {res}  3637.24
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 89:(Std. Err. adjusted for {res:5,431} clusters in HHID_panel)}
{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 25}{c |}{col 37}    Robust
{col 1}                   hdd9{col 25}{c |}      Coef.{col 37}   Std. Err.{col 49}      z{col 57}   P>|z|{col 65}     [95% Con{col 78}f. Interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 19}pdd9 {c |}{col 25}{res}{space 2} .0111538{col 37}{space 2} .0130321{col 48}{space 1}    0.86{col 57}{space 3}0.392{col 65}{space 4}-.0143886{col 78}{space 3} .0366963
{txt}{space 9}dist_popcenter {c |}{col 25}{res}{space 2}-.0039446{col 37}{space 2} .0006251{col 48}{space 1}   -6.31{col 57}{space 3}0.000{col 65}{space 4}-.0051697{col 78}{space 3}-.0027195
{txt}{space 23} {c |}
c.pdd9#c.dist_popcenter {c |}{col 25}{res}{space 2} .0010726{col 37}{space 2} .0002011{col 48}{space 1}    5.33{col 57}{space 3}0.000{col 65}{space 4} .0006784{col 78}{space 3} .0014668
{txt}{space 23} {c |}
{space 17}hhsize {c |}{col 25}{res}{space 2} .0480129{col 37}{space 2} .0069837{col 48}{space 1}    6.88{col 57}{space 3}0.000{col 65}{space 4} .0343252{col 78}{space 3} .0617006
{txt}{space 8}dependent_share {c |}{col 25}{res}{space 2}-.0153151{col 37}{space 2} .0538723{col 48}{space 1}   -0.28{col 57}{space 3}0.776{col 65}{space 4}-.1209028{col 78}{space 3} .0902726
{txt}{space 15}head_age {c |}{col 25}{res}{space 2}-.0028796{col 37}{space 2} .0009423{col 48}{space 1}   -3.06{col 57}{space 3}0.002{col 65}{space 4}-.0047264{col 78}{space 3}-.0010328
{txt}{space 12}female_head {c |}{col 25}{res}{space 2}-.0146457{col 37}{space 2}  .033027{col 48}{space 1}   -0.44{col 57}{space 3}0.657{col 65}{space 4}-.0793776{col 78}{space 3} .0500861
{txt}{space 14}head_read {c |}{col 25}{res}{space 2} .3959678{col 37}{space 2} .0300212{col 48}{space 1}   13.19{col 57}{space 3}0.000{col 65}{space 4} .3371272{col 78}{space 3} .4548083
{txt}{space 15}motobike {c |}{col 25}{res}{space 2}-.1411132{col 37}{space 2} .1323959{col 48}{space 1}   -1.07{col 57}{space 3}0.286{col 65}{space 4}-.4006044{col 78}{space 3} .1183779
{txt}{space 18}phone {c |}{col 25}{res}{space 2} .1884775{col 37}{space 2} .0369884{col 48}{space 1}    5.10{col 57}{space 3}0.000{col 65}{space 4} .1159815{col 78}{space 3} .2609734
{txt}{space 12}electricity {c |}{col 25}{res}{space 2} .1419862{col 37}{space 2} .0451709{col 48}{space 1}    3.14{col 57}{space 3}0.002{col 65}{space 4}  .053453{col 78}{space 3} .2305195
{txt}{space 16}wagejob {c |}{col 25}{res}{space 2} -.037266{col 37}{space 2} .0536996{col 48}{space 1}   -0.69{col 57}{space 3}0.488{col 65}{space 4}-.1425153{col 78}{space 3} .0679834
{txt}{space 13}enterprise {c |}{col 25}{res}{space 2} .2112543{col 37}{space 2} .0472998{col 48}{space 1}    4.47{col 57}{space 3}0.000{col 65}{space 4} .1185484{col 78}{space 3} .3039602
{txt}{space 10}weather_shock {c |}{col 25}{res}{space 2}  -.15913{col 37}{space 2} .0294416{col 48}{space 1}   -5.40{col 57}{space 3}0.000{col 65}{space 4}-.2168346{col 78}{space 3}-.1014255
{txt}{space 14}plot_area {c |}{col 25}{res}{space 2} .0056281{col 37}{space 2} .0035341{col 48}{space 1}    1.59{col 57}{space 3}0.111{col 65}{space 4}-.0012986{col 78}{space 3} .0125548
{txt}{space 13}other_crop {c |}{col 25}{res}{space 2} .2095101{col 37}{space 2} .0312129{col 48}{space 1}    6.71{col 57}{space 3}0.000{col 65}{space 4}  .148334{col 78}{space 3} .2706863
{txt}{space 10}motobike_mean {c |}{col 25}{res}{space 2}  1.15204{col 37}{space 2} .2148533{col 48}{space 1}    5.36{col 57}{space 3}0.000{col 65}{space 4} .7309354{col 78}{space 3} 1.573145
{txt}{space 13}phone_mean {c |}{col 25}{res}{space 2} .5332277{col 37}{space 2} .0560909{col 48}{space 1}    9.51{col 57}{space 3}0.000{col 65}{space 4} .4232914{col 78}{space 3} .6431639
{txt}{space 7}electricity_mean {c |}{col 25}{res}{space 2} .6155916{col 37}{space 2}  .067693{col 48}{space 1}    9.09{col 57}{space 3}0.000{col 65}{space 4} .4829158{col 78}{space 3} .7482674
{txt}{space 11}wagejob_mean {c |}{col 25}{res}{space 2} .4808063{col 37}{space 2} .0811485{col 48}{space 1}    5.93{col 57}{space 3}0.000{col 65}{space 4} .3217581{col 78}{space 3} .6398544
{txt}{space 8}enterprise_mean {c |}{col 25}{res}{space 2} .0927379{col 37}{space 2} .0598739{col 48}{space 1}    1.55{col 57}{space 3}0.121{col 65}{space 4}-.0246128{col 78}{space 3} .2100885
{txt}{space 14}pdd9_mean {c |}{col 25}{res}{space 2} .0058738{col 37}{space 2} .0143358{col 48}{space 1}    0.41{col 57}{space 3}0.682{col 65}{space 4}-.0222238{col 78}{space 3} .0339715
{txt}{space 17}year_6 {c |}{col 25}{res}{space 2}-.1967094{col 37}{space 2} .0211832{col 48}{space 1}   -9.29{col 57}{space 3}0.000{col 65}{space 4}-.2382276{col 78}{space 3}-.1551911
{txt}{space 18}_cons {c |}{col 25}{res}{space 2} 3.328664{col 37}{space 2} .0734337{col 48}{space 1}   45.33{col 57}{space 3}0.000{col 65}{space 4} 3.184737{col 78}{space 3} 3.472592
{txt}{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                sigma_u {c |} {res}  .7578622
                {txt}sigma_e {c |} {res} 1.1129921
                    {txt}rho {c |} {res} .31677957{txt}   (fraction of variance due to u_i)
{hline 24}{c BT}{hline 64}

{com}. eststo est2
{txt}
{com}. 
. 
. xtreg hdd9  c.pdd9##c.dist_popcenter   $xlist  pdd9_mean year_3  if country==6, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     3,543
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     2,033

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0425                                         {txt}min = {res}         1
{txt}     between = {res}0.3367                                         {txt}avg = {res}       1.7
{txt}     overall = {res}0.2818                                         {txt}max = {res}         2

                                                {txt}Wald chi2({res}23{txt})     =  {res}  1423.53
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 89:(Std. Err. adjusted for {res:2,033} clusters in HHID_panel)}
{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 25}{c |}{col 37}    Robust
{col 1}                   hdd9{col 25}{c |}      Coef.{col 37}   Std. Err.{col 49}      z{col 57}   P>|z|{col 65}     [95% Con{col 78}f. Interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 19}pdd9 {c |}{col 25}{res}{space 2} .0827994{col 37}{space 2} .0354003{col 48}{space 1}    2.34{col 57}{space 3}0.019{col 65}{space 4}  .013416{col 78}{space 3} .1521827
{txt}{space 9}dist_popcenter {c |}{col 25}{res}{space 2}-.0100045{col 37}{space 2} .0026128{col 48}{space 1}   -3.83{col 57}{space 3}0.000{col 65}{space 4}-.0151256{col 78}{space 3}-.0048835
{txt}{space 23} {c |}
c.pdd9#c.dist_popcenter {c |}{col 25}{res}{space 2} .0021659{col 37}{space 2} .0007177{col 48}{space 1}    3.02{col 57}{space 3}0.003{col 65}{space 4} .0007593{col 78}{space 3} .0035724
{txt}{space 23} {c |}
{space 17}hhsize {c |}{col 25}{res}{space 2}-.0106603{col 37}{space 2} .0132161{col 48}{space 1}   -0.81{col 57}{space 3}0.420{col 65}{space 4}-.0365633{col 78}{space 3} .0152427
{txt}{space 8}dependent_share {c |}{col 25}{res}{space 2}-.4013238{col 37}{space 2} .1202561{col 48}{space 1}   -3.34{col 57}{space 3}0.001{col 65}{space 4}-.6370214{col 78}{space 3}-.1656262
{txt}{space 15}head_age {c |}{col 25}{res}{space 2}-.0043987{col 37}{space 2} .0018859{col 48}{space 1}   -2.33{col 57}{space 3}0.020{col 65}{space 4}-.0080951{col 78}{space 3}-.0007024
{txt}{space 12}female_head {c |}{col 25}{res}{space 2}-.1499849{col 37}{space 2} .0662149{col 48}{space 1}   -2.27{col 57}{space 3}0.024{col 65}{space 4}-.2797638{col 78}{space 3}-.0202061
{txt}{space 14}head_read {c |}{col 25}{res}{space 2} .3506916{col 37}{space 2} .0649948{col 48}{space 1}    5.40{col 57}{space 3}0.000{col 65}{space 4} .2233042{col 78}{space 3} .4780789
{txt}{space 15}motobike {c |}{col 25}{res}{space 2} .2528945{col 37}{space 2} .3840555{col 48}{space 1}    0.66{col 57}{space 3}0.510{col 65}{space 4}-.4998404{col 78}{space 3} 1.005629
{txt}{space 18}phone {c |}{col 25}{res}{space 2} .2345152{col 37}{space 2} .0987117{col 48}{space 1}    2.38{col 57}{space 3}0.018{col 65}{space 4} .0410438{col 78}{space 3} .4279867
{txt}{space 12}electricity {c |}{col 25}{res}{space 2} .7214999{col 37}{space 2} .1823086{col 48}{space 1}    3.96{col 57}{space 3}0.000{col 65}{space 4} .3641816{col 78}{space 3} 1.078818
{txt}{space 16}wagejob {c |}{col 25}{res}{space 2} .1690347{col 37}{space 2} .1087344{col 48}{space 1}    1.55{col 57}{space 3}0.120{col 65}{space 4}-.0440809{col 78}{space 3} .3821503
{txt}{space 13}enterprise {c |}{col 25}{res}{space 2} .2481533{col 37}{space 2} .0780706{col 48}{space 1}    3.18{col 57}{space 3}0.001{col 65}{space 4} .0951377{col 78}{space 3}  .401169
{txt}{space 10}weather_shock {c |}{col 25}{res}{space 2}-.1644838{col 37}{space 2} .0534949{col 48}{space 1}   -3.07{col 57}{space 3}0.002{col 65}{space 4}-.2693318{col 78}{space 3}-.0596358
{txt}{space 14}plot_area {c |}{col 25}{res}{space 2} .0366957{col 37}{space 2}  .042247{col 48}{space 1}    0.87{col 57}{space 3}0.385{col 65}{space 4}-.0461069{col 78}{space 3} .1194984
{txt}{space 13}other_crop {c |}{col 25}{res}{space 2}-.0140805{col 37}{space 2} .0733392{col 48}{space 1}   -0.19{col 57}{space 3}0.848{col 65}{space 4}-.1578228{col 78}{space 3} .1296618
{txt}{space 10}motobike_mean {c |}{col 25}{res}{space 2}-.0894115{col 37}{space 2} .4792901{col 48}{space 1}   -0.19{col 57}{space 3}0.852{col 65}{space 4}-1.028803{col 78}{space 3} .8499799
{txt}{space 13}phone_mean {c |}{col 25}{res}{space 2}  .410412{col 37}{space 2} .1231474{col 48}{space 1}    3.33{col 57}{space 3}0.001{col 65}{space 4} .1690475{col 78}{space 3} .6517765
{txt}{space 7}electricity_mean {c |}{col 25}{res}{space 2} .3264455{col 37}{space 2} .2066123{col 48}{space 1}    1.58{col 57}{space 3}0.114{col 65}{space 4}-.0785072{col 78}{space 3} .7313983
{txt}{space 11}wagejob_mean {c |}{col 25}{res}{space 2} .3133972{col 37}{space 2} .1331393{col 48}{space 1}    2.35{col 57}{space 3}0.019{col 65}{space 4}  .052449{col 78}{space 3} .5743453
{txt}{space 8}enterprise_mean {c |}{col 25}{res}{space 2}  .278429{col 37}{space 2} .1064804{col 48}{space 1}    2.61{col 57}{space 3}0.009{col 65}{space 4} .0697313{col 78}{space 3} .4871267
{txt}{space 14}pdd9_mean {c |}{col 25}{res}{space 2}-.0454976{col 37}{space 2} .0351965{col 48}{space 1}   -1.29{col 57}{space 3}0.196{col 65}{space 4}-.1144816{col 78}{space 3} .0234863
{txt}{space 17}year_3 {c |}{col 25}{res}{space 2} .0349143{col 37}{space 2} .0460874{col 48}{space 1}    0.76{col 57}{space 3}0.449{col 65}{space 4}-.0554153{col 78}{space 3} .1252439
{txt}{space 18}_cons {c |}{col 25}{res}{space 2} 5.685997{col 37}{space 2} .1454005{col 48}{space 1}   39.11{col 57}{space 3}0.000{col 65}{space 4} 5.401017{col 78}{space 3} 5.970977
{txt}{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                sigma_u {c |} {res} .67898512
                {txt}sigma_e {c |} {res} 1.2700233
                    {txt}rho {c |} {res} .22228798{txt}   (fraction of variance due to u_i)
{hline 24}{c BT}{hline 64}

{com}. eststo est3
{txt}
{com}. 
.  
. xtreg hdd9  c.pdd9##c.dist_popcenter    $xlist  pdd9_mean  year_4 if country==1, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     6,907
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     3,930

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0394                                         {txt}min = {res}         1
{txt}     between = {res}0.2705                                         {txt}avg = {res}       1.8
{txt}     overall = {res}0.2108                                         {txt}max = {res}         2

                                                {txt}Wald chi2({res}23{txt})     =  {res}  1802.45
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 89:(Std. Err. adjusted for {res:3,930} clusters in HHID_panel)}
{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 25}{c |}{col 37}    Robust
{col 1}                   hdd9{col 25}{c |}      Coef.{col 37}   Std. Err.{col 49}      z{col 57}   P>|z|{col 65}     [95% Con{col 78}f. Interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 19}pdd9 {c |}{col 25}{res}{space 2} .1382103{col 37}{space 2} .0379527{col 48}{space 1}    3.64{col 57}{space 3}0.000{col 65}{space 4} .0638244{col 78}{space 3} .2125962
{txt}{space 9}dist_popcenter {c |}{col 25}{res}{space 2}-.0079583{col 37}{space 2} .0007506{col 48}{space 1}  -10.60{col 57}{space 3}0.000{col 65}{space 4}-.0094294{col 78}{space 3}-.0064872
{txt}{space 23} {c |}
c.pdd9#c.dist_popcenter {c |}{col 25}{res}{space 2} .0018045{col 37}{space 2} .0003005{col 48}{space 1}    6.00{col 57}{space 3}0.000{col 65}{space 4} .0012155{col 78}{space 3} .0023936
{txt}{space 23} {c |}
{space 17}hhsize {c |}{col 25}{res}{space 2} .0156538{col 37}{space 2} .0063491{col 48}{space 1}    2.47{col 57}{space 3}0.014{col 65}{space 4} .0032098{col 78}{space 3} .0280978
{txt}{space 8}dependent_share {c |}{col 25}{res}{space 2}-.0231958{col 37}{space 2} .0969981{col 48}{space 1}   -0.24{col 57}{space 3}0.811{col 65}{space 4}-.2133087{col 78}{space 3}  .166917
{txt}{space 15}head_age {c |}{col 25}{res}{space 2} .0024271{col 37}{space 2}  .001384{col 48}{space 1}    1.75{col 57}{space 3}0.079{col 65}{space 4}-.0002855{col 78}{space 3} .0051396
{txt}{space 12}female_head {c |}{col 25}{res}{space 2} .1198442{col 37}{space 2} .0572526{col 48}{space 1}    2.09{col 57}{space 3}0.036{col 65}{space 4} .0076311{col 78}{space 3} .2320574
{txt}{space 14}head_read {c |}{col 25}{res}{space 2} .3181767{col 37}{space 2} .0438492{col 48}{space 1}    7.26{col 57}{space 3}0.000{col 65}{space 4} .2322339{col 78}{space 3} .4041196
{txt}{space 15}motobike {c |}{col 25}{res}{space 2} .2446147{col 37}{space 2} .0963321{col 48}{space 1}    2.54{col 57}{space 3}0.011{col 65}{space 4} .0558073{col 78}{space 3} .4334222
{txt}{space 18}phone {c |}{col 25}{res}{space 2} .0976581{col 37}{space 2} .0746189{col 48}{space 1}    1.31{col 57}{space 3}0.191{col 65}{space 4}-.0485922{col 78}{space 3} .2439083
{txt}{space 12}electricity {c |}{col 25}{res}{space 2} .2136692{col 37}{space 2} .1062976{col 48}{space 1}    2.01{col 57}{space 3}0.044{col 65}{space 4} .0053297{col 78}{space 3} .4220087
{txt}{space 16}wagejob {c |}{col 25}{res}{space 2} .2167708{col 37}{space 2} .0840985{col 48}{space 1}    2.58{col 57}{space 3}0.010{col 65}{space 4} .0519407{col 78}{space 3} .3816009
{txt}{space 13}enterprise {c |}{col 25}{res}{space 2}-.1735673{col 37}{space 2} .0654069{col 48}{space 1}   -2.65{col 57}{space 3}0.008{col 65}{space 4}-.3017625{col 78}{space 3} -.045372
{txt}{space 10}weather_shock {c |}{col 25}{res}{space 2}-.0863862{col 37}{space 2}  .044613{col 48}{space 1}   -1.94{col 57}{space 3}0.053{col 65}{space 4}-.1738261{col 78}{space 3} .0010537
{txt}{space 14}plot_area {c |}{col 25}{res}{space 2}-.0014702{col 37}{space 2} .0015335{col 48}{space 1}   -0.96{col 57}{space 3}0.338{col 65}{space 4}-.0044758{col 78}{space 3} .0015354
{txt}{space 13}other_crop {c |}{col 25}{res}{space 2} .1746848{col 37}{space 2} .2159626{col 48}{space 1}    0.81{col 57}{space 3}0.419{col 65}{space 4}-.2485941{col 78}{space 3} .5979637
{txt}{space 10}motobike_mean {c |}{col 25}{res}{space 2} .1249374{col 37}{space 2}  .119406{col 48}{space 1}    1.05{col 57}{space 3}0.295{col 65}{space 4}-.1090941{col 78}{space 3} .3589688
{txt}{space 13}phone_mean {c |}{col 25}{res}{space 2} .2123145{col 37}{space 2} .0928687{col 48}{space 1}    2.29{col 57}{space 3}0.022{col 65}{space 4} .0302952{col 78}{space 3} .3943338
{txt}{space 7}electricity_mean {c |}{col 25}{res}{space 2} .3758815{col 37}{space 2} .1255037{col 48}{space 1}    2.99{col 57}{space 3}0.003{col 65}{space 4} .1298989{col 78}{space 3} .6218642
{txt}{space 11}wagejob_mean {c |}{col 25}{res}{space 2} .0723677{col 37}{space 2} .1042664{col 48}{space 1}    0.69{col 57}{space 3}0.488{col 65}{space 4}-.1319907{col 78}{space 3} .2767261
{txt}{space 8}enterprise_mean {c |}{col 25}{res}{space 2} .3152715{col 37}{space 2} .0813926{col 48}{space 1}    3.87{col 57}{space 3}0.000{col 65}{space 4} .1557449{col 78}{space 3}  .474798
{txt}{space 14}pdd9_mean {c |}{col 25}{res}{space 2}-.2217967{col 37}{space 2} .0394361{col 48}{space 1}   -5.62{col 57}{space 3}0.000{col 65}{space 4}-.2990899{col 78}{space 3}-.1445034
{txt}{space 17}year_4 {c |}{col 25}{res}{space 2} .2649808{col 37}{space 2} .0368617{col 48}{space 1}    7.19{col 57}{space 3}0.000{col 65}{space 4} .1927332{col 78}{space 3} .3372284
{txt}{space 18}_cons {c |}{col 25}{res}{space 2} 5.061248{col 37}{space 2} .1182241{col 48}{space 1}   42.81{col 57}{space 3}0.000{col 65}{space 4} 4.829533{col 78}{space 3} 5.292963
{txt}{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                sigma_u {c |} {res}  .5606369
                {txt}sigma_e {c |} {res} 1.3703622
                    {txt}rho {c |} {res}  .1433778{txt}   (fraction of variance due to u_i)
{hline 24}{c BT}{hline 64}

{com}. eststo est4
{txt}
{com}. 
. 
. xtreg hdd9  c.pdd9##c.dist_popcenter    $xlist  pdd9_mean  year_3 year_5 year_8 if country==2, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    18,590
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     8,222

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0390                                         {txt}min = {res}         1
{txt}     between = {res}0.3105                                         {txt}avg = {res}       2.3
{txt}     overall = {res}0.2633                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}25{txt})     =  {res}  4940.79
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 89:(Std. Err. adjusted for {res:8,222} clusters in HHID_panel)}
{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 25}{c |}{col 37}    Robust
{col 1}                   hdd9{col 25}{c |}      Coef.{col 37}   Std. Err.{col 49}      z{col 57}   P>|z|{col 65}     [95% Con{col 78}f. Interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 19}pdd9 {c |}{col 25}{res}{space 2} .0993216{col 37}{space 2} .0163849{col 48}{space 1}    6.06{col 57}{space 3}0.000{col 65}{space 4} .0672077{col 78}{space 3} .1314354
{txt}{space 9}dist_popcenter {c |}{col 25}{res}{space 2}-.0021647{col 37}{space 2} .0010417{col 48}{space 1}   -2.08{col 57}{space 3}0.038{col 65}{space 4}-.0042064{col 78}{space 3}-.0001229
{txt}{space 23} {c |}
c.pdd9#c.dist_popcenter {c |}{col 25}{res}{space 2}-.0001038{col 37}{space 2} .0004242{col 48}{space 1}   -0.24{col 57}{space 3}0.807{col 65}{space 4}-.0009352{col 78}{space 3} .0007276
{txt}{space 23} {c |}
{space 17}hhsize {c |}{col 25}{res}{space 2}-.0249194{col 37}{space 2} .0044453{col 48}{space 1}   -5.61{col 57}{space 3}0.000{col 65}{space 4} -.033632{col 78}{space 3}-.0162068
{txt}{space 8}dependent_share {c |}{col 25}{res}{space 2} .1391867{col 37}{space 2} .0489418{col 48}{space 1}    2.84{col 57}{space 3}0.004{col 65}{space 4} .0432626{col 78}{space 3} .2351109
{txt}{space 15}head_age {c |}{col 25}{res}{space 2}  .004382{col 37}{space 2} .0009019{col 48}{space 1}    4.86{col 57}{space 3}0.000{col 65}{space 4} .0026143{col 78}{space 3} .0061498
{txt}{space 12}female_head {c |}{col 25}{res}{space 2} .2167186{col 37}{space 2} .0350653{col 48}{space 1}    6.18{col 57}{space 3}0.000{col 65}{space 4} .1479918{col 78}{space 3} .2854454
{txt}{space 14}head_read {c |}{col 25}{res}{space 2} .1920503{col 37}{space 2} .0272126{col 48}{space 1}    7.06{col 57}{space 3}0.000{col 65}{space 4} .1387145{col 78}{space 3} .2453861
{txt}{space 15}motobike {c |}{col 25}{res}{space 2} .0372139{col 37}{space 2} .0383438{col 48}{space 1}    0.97{col 57}{space 3}0.332{col 65}{space 4}-.0379384{col 78}{space 3} .1123663
{txt}{space 18}phone {c |}{col 25}{res}{space 2} .1856972{col 37}{space 2} .0383036{col 48}{space 1}    4.85{col 57}{space 3}0.000{col 65}{space 4} .1106235{col 78}{space 3} .2607708
{txt}{space 12}electricity {c |}{col 25}{res}{space 2} .0842125{col 37}{space 2} .0446496{col 48}{space 1}    1.89{col 57}{space 3}0.059{col 65}{space 4}-.0032992{col 78}{space 3} .1717242
{txt}{space 16}wagejob {c |}{col 25}{res}{space 2} .2138857{col 37}{space 2} .0480874{col 48}{space 1}    4.45{col 57}{space 3}0.000{col 65}{space 4}  .119636{col 78}{space 3} .3081353
{txt}{space 13}enterprise {c |}{col 25}{res}{space 2} .2779726{col 37}{space 2} .0390379{col 48}{space 1}    7.12{col 57}{space 3}0.000{col 65}{space 4} .2014597{col 78}{space 3} .3544855
{txt}{space 10}weather_shock {c |}{col 25}{res}{space 2}-.0053992{col 37}{space 2} .0466791{col 48}{space 1}   -0.12{col 57}{space 3}0.908{col 65}{space 4}-.0968886{col 78}{space 3} .0860902
{txt}{space 14}plot_area {c |}{col 25}{res}{space 2}-.0092658{col 37}{space 2} .0067626{col 48}{space 1}   -1.37{col 57}{space 3}0.171{col 65}{space 4}-.0225202{col 78}{space 3} .0039886
{txt}{space 13}other_crop {c |}{col 25}{res}{space 2} .3139542{col 37}{space 2} .0599772{col 48}{space 1}    5.23{col 57}{space 3}0.000{col 65}{space 4} .1964011{col 78}{space 3} .4315074
{txt}{space 10}motobike_mean {c |}{col 25}{res}{space 2}-.0533782{col 37}{space 2} .0533127{col 48}{space 1}   -1.00{col 57}{space 3}0.317{col 65}{space 4}-.1578691{col 78}{space 3} .0511128
{txt}{space 13}phone_mean {c |}{col 25}{res}{space 2} .8125325{col 37}{space 2}  .058538{col 48}{space 1}   13.88{col 57}{space 3}0.000{col 65}{space 4} .6978001{col 78}{space 3} .9272648
{txt}{space 7}electricity_mean {c |}{col 25}{res}{space 2} .8372002{col 37}{space 2} .0576522{col 48}{space 1}   14.52{col 57}{space 3}0.000{col 65}{space 4}  .724204{col 78}{space 3} .9501964
{txt}{space 11}wagejob_mean {c |}{col 25}{res}{space 2} .2476453{col 37}{space 2} .0638858{col 48}{space 1}    3.88{col 57}{space 3}0.000{col 65}{space 4} .1224314{col 78}{space 3} .3728592
{txt}{space 8}enterprise_mean {c |}{col 25}{res}{space 2} -.010171{col 37}{space 2} .0511284{col 48}{space 1}   -0.20{col 57}{space 3}0.842{col 65}{space 4}-.1103809{col 78}{space 3} .0900389
{txt}{space 14}pdd9_mean {c |}{col 25}{res}{space 2}-.0768763{col 37}{space 2} .0181919{col 48}{space 1}   -4.23{col 57}{space 3}0.000{col 65}{space 4}-.1125317{col 78}{space 3} -.041221
{txt}{space 17}year_3 {c |}{col 25}{res}{space 2}-.5915484{col 37}{space 2} .0311591{col 48}{space 1}  -18.98{col 57}{space 3}0.000{col 65}{space 4}-.6526191{col 78}{space 3}-.5304778
{txt}{space 17}year_5 {c |}{col 25}{res}{space 2}-.4981683{col 37}{space 2} .0312781{col 48}{space 1}  -15.93{col 57}{space 3}0.000{col 65}{space 4}-.5594722{col 78}{space 3}-.4368644
{txt}{space 17}year_8 {c |}{col 25}{res}{space 2}-.3311327{col 37}{space 2} .0308613{col 48}{space 1}  -10.73{col 57}{space 3}0.000{col 65}{space 4}-.3916197{col 78}{space 3}-.2706456
{txt}{space 18}_cons {c |}{col 25}{res}{space 2} 4.589415{col 37}{space 2} .0785149{col 48}{space 1}   58.45{col 57}{space 3}0.000{col 65}{space 4} 4.435529{col 78}{space 3} 4.743302
{txt}{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                sigma_u {c |} {res}  .8589988
                {txt}sigma_e {c |} {res} 1.2345132
                    {txt}rho {c |} {res} .32622058{txt}   (fraction of variance due to u_i)
{hline 24}{c BT}{hline 64}

{com}. eststo est5
{txt}
{com}. 
. 
. xtreg hdd9  c.pdd9##c.dist_popcenter   $xlist  pdd9_mean year_1 year_3  if country==5, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    11,364
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     5,101

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0295                                         {txt}min = {res}         1
{txt}     between = {res}0.2532                                         {txt}avg = {res}       2.2
{txt}     overall = {res}0.2147                                         {txt}max = {res}         3

                                                {txt}Wald chi2({res}24{txt})     =  {res}  2307.66
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 89:(Std. Err. adjusted for {res:5,101} clusters in HHID_panel)}
{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 25}{c |}{col 37}    Robust
{col 1}                   hdd9{col 25}{c |}      Coef.{col 37}   Std. Err.{col 49}      z{col 57}   P>|z|{col 65}     [95% Con{col 78}f. Interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 19}pdd9 {c |}{col 25}{res}{space 2} .0895012{col 37}{space 2} .0166281{col 48}{space 1}    5.38{col 57}{space 3}0.000{col 65}{space 4} .0569108{col 78}{space 3} .1220916
{txt}{space 9}dist_popcenter {c |}{col 25}{res}{space 2}-.0045376{col 37}{space 2} .0008088{col 48}{space 1}   -5.61{col 57}{space 3}0.000{col 65}{space 4}-.0061228{col 78}{space 3}-.0029525
{txt}{space 23} {c |}
c.pdd9#c.dist_popcenter {c |}{col 25}{res}{space 2} .0004662{col 37}{space 2} .0001846{col 48}{space 1}    2.52{col 57}{space 3}0.012{col 65}{space 4} .0001043{col 78}{space 3} .0008281
{txt}{space 23} {c |}
{space 17}hhsize {c |}{col 25}{res}{space 2} .0039849{col 37}{space 2} .0056103{col 48}{space 1}    0.71{col 57}{space 3}0.478{col 65}{space 4} -.007011{col 78}{space 3} .0149808
{txt}{space 8}dependent_share {c |}{col 25}{res}{space 2} .1318819{col 37}{space 2} .0710391{col 48}{space 1}    1.86{col 57}{space 3}0.063{col 65}{space 4} -.007352{col 78}{space 3} .2711159
{txt}{space 15}head_age {c |}{col 25}{res}{space 2}-.0035287{col 37}{space 2} .0011137{col 48}{space 1}   -3.17{col 57}{space 3}0.002{col 65}{space 4}-.0057116{col 78}{space 3}-.0013458
{txt}{space 12}female_head {c |}{col 25}{res}{space 2} .0749686{col 37}{space 2} .0381213{col 48}{space 1}    1.97{col 57}{space 3}0.049{col 65}{space 4} .0002522{col 78}{space 3} .1496851
{txt}{space 14}head_read {c |}{col 25}{res}{space 2} .2903883{col 37}{space 2}  .038584{col 48}{space 1}    7.53{col 57}{space 3}0.000{col 65}{space 4} .2147651{col 78}{space 3} .3660115
{txt}{space 15}motobike {c |}{col 25}{res}{space 2}  .121971{col 37}{space 2} .0848089{col 48}{space 1}    1.44{col 57}{space 3}0.150{col 65}{space 4}-.0442514{col 78}{space 3} .2881934
{txt}{space 18}phone {c |}{col 25}{res}{space 2} .2573053{col 37}{space 2} .0484235{col 48}{space 1}    5.31{col 57}{space 3}0.000{col 65}{space 4} .1623969{col 78}{space 3} .3522136
{txt}{space 12}electricity {c |}{col 25}{res}{space 2} .1381779{col 37}{space 2} .0834902{col 48}{space 1}    1.66{col 57}{space 3}0.098{col 65}{space 4}-.0254599{col 78}{space 3} .3018157
{txt}{space 16}wagejob {c |}{col 25}{res}{space 2} .1130704{col 37}{space 2} .0392125{col 48}{space 1}    2.88{col 57}{space 3}0.004{col 65}{space 4} .0362153{col 78}{space 3} .1899255
{txt}{space 13}enterprise {c |}{col 25}{res}{space 2}  .198002{col 37}{space 2} .0408317{col 48}{space 1}    4.85{col 57}{space 3}0.000{col 65}{space 4} .1179734{col 78}{space 3} .2780307
{txt}{space 10}weather_shock {c |}{col 25}{res}{space 2}-.0123028{col 37}{space 2} .0402882{col 48}{space 1}   -0.31{col 57}{space 3}0.760{col 65}{space 4}-.0912662{col 78}{space 3} .0666607
{txt}{space 14}plot_area {c |}{col 25}{res}{space 2} .0026366{col 37}{space 2} .0021078{col 48}{space 1}    1.25{col 57}{space 3}0.211{col 65}{space 4}-.0014946{col 78}{space 3} .0067677
{txt}{space 13}other_crop {c |}{col 25}{res}{space 2}-.0117849{col 37}{space 2} .0384253{col 48}{space 1}   -0.31{col 57}{space 3}0.759{col 65}{space 4}-.0870971{col 78}{space 3} .0635272
{txt}{space 10}motobike_mean {c |}{col 25}{res}{space 2}  .464568{col 37}{space 2} .1104582{col 48}{space 1}    4.21{col 57}{space 3}0.000{col 65}{space 4}  .248074{col 78}{space 3}  .681062
{txt}{space 13}phone_mean {c |}{col 25}{res}{space 2} .5846241{col 37}{space 2} .0676201{col 48}{space 1}    8.65{col 57}{space 3}0.000{col 65}{space 4} .4520911{col 78}{space 3} .7171571
{txt}{space 7}electricity_mean {c |}{col 25}{res}{space 2} .5213169{col 37}{space 2} .0985994{col 48}{space 1}    5.29{col 57}{space 3}0.000{col 65}{space 4} .3280656{col 78}{space 3} .7145683
{txt}{space 11}wagejob_mean {c |}{col 25}{res}{space 2} .0475389{col 37}{space 2} .0575804{col 48}{space 1}    0.83{col 57}{space 3}0.409{col 65}{space 4}-.0653165{col 78}{space 3} .1603944
{txt}{space 8}enterprise_mean {c |}{col 25}{res}{space 2} .1951055{col 37}{space 2} .0584226{col 48}{space 1}    3.34{col 57}{space 3}0.001{col 65}{space 4} .0805994{col 78}{space 3} .3096116
{txt}{space 14}pdd9_mean {c |}{col 25}{res}{space 2}  -.03724{col 37}{space 2} .0179113{col 48}{space 1}   -2.08{col 57}{space 3}0.038{col 65}{space 4}-.0723454{col 78}{space 3}-.0021345
{txt}{space 17}year_1 {c |}{col 25}{res}{space 2}-.0203283{col 37}{space 2} .0333094{col 48}{space 1}   -0.61{col 57}{space 3}0.542{col 65}{space 4}-.0856135{col 78}{space 3} .0449568
{txt}{space 17}year_3 {c |}{col 25}{res}{space 2} .1046363{col 37}{space 2} .0276932{col 48}{space 1}    3.78{col 57}{space 3}0.000{col 65}{space 4} .0503586{col 78}{space 3} .1589141
{txt}{space 18}_cons {c |}{col 25}{res}{space 2} 4.700038{col 37}{space 2} .0923969{col 48}{space 1}   50.87{col 57}{space 3}0.000{col 65}{space 4} 4.518943{col 78}{space 3} 4.881132
{txt}{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                sigma_u {c |} {res} .83080347
                {txt}sigma_e {c |} {res} 1.2099937
                    {txt}rho {c |} {res} .32039563{txt}   (fraction of variance due to u_i)
{hline 24}{c BT}{hline 64}

{com}. eststo est6
{txt}
{com}. 
. xtreg hdd9  c.pdd9##c.dist_popcenter   $xlist  pdd9_mean  year_2 year_3  if country==4, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     8,018
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     3,077

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0173                                         {txt}min = {res}         1
{txt}     between = {res}0.2688                                         {txt}avg = {res}       2.6
{txt}     overall = {res}0.1966                                         {txt}max = {res}         3

                                                {txt}Wald chi2({res}24{txt})     =  {res}  1387.96
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 89:(Std. Err. adjusted for {res:3,077} clusters in HHID_panel)}
{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 25}{c |}{col 37}    Robust
{col 1}                   hdd9{col 25}{c |}      Coef.{col 37}   Std. Err.{col 49}      z{col 57}   P>|z|{col 65}     [95% Con{col 78}f. Interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 19}pdd9 {c |}{col 25}{res}{space 2} .0421998{col 37}{space 2} .0249763{col 48}{space 1}    1.69{col 57}{space 3}0.091{col 65}{space 4}-.0067528{col 78}{space 3} .0911525
{txt}{space 9}dist_popcenter {c |}{col 25}{res}{space 2}-.0142293{col 37}{space 2} .0023723{col 48}{space 1}   -6.00{col 57}{space 3}0.000{col 65}{space 4} -.018879{col 78}{space 3}-.0095796
{txt}{space 23} {c |}
c.pdd9#c.dist_popcenter {c |}{col 25}{res}{space 2} .0015099{col 37}{space 2} .0006556{col 48}{space 1}    2.30{col 57}{space 3}0.021{col 65}{space 4}  .000225{col 78}{space 3} .0027948
{txt}{space 23} {c |}
{space 17}hhsize {c |}{col 25}{res}{space 2}  .022239{col 37}{space 2} .0074805{col 48}{space 1}    2.97{col 57}{space 3}0.003{col 65}{space 4} .0075775{col 78}{space 3} .0369004
{txt}{space 8}dependent_share {c |}{col 25}{res}{space 2} .1137123{col 37}{space 2} .0927412{col 48}{space 1}    1.23{col 57}{space 3}0.220{col 65}{space 4}-.0680572{col 78}{space 3} .2954817
{txt}{space 15}head_age {c |}{col 25}{res}{space 2}-.0068808{col 37}{space 2} .0013985{col 48}{space 1}   -4.92{col 57}{space 3}0.000{col 65}{space 4}-.0096218{col 78}{space 3}-.0041397
{txt}{space 12}female_head {c |}{col 25}{res}{space 2}-.0776194{col 37}{space 2}  .046654{col 48}{space 1}   -1.66{col 57}{space 3}0.096{col 65}{space 4}-.1690597{col 78}{space 3} .0138208
{txt}{space 14}head_read {c |}{col 25}{res}{space 2} .2107113{col 37}{space 2} .0468555{col 48}{space 1}    4.50{col 57}{space 3}0.000{col 65}{space 4} .1188762{col 78}{space 3} .3025464
{txt}{space 15}motobike {c |}{col 25}{res}{space 2} .0642154{col 37}{space 2} .0870374{col 48}{space 1}    0.74{col 57}{space 3}0.461{col 65}{space 4}-.1063748{col 78}{space 3} .2348056
{txt}{space 18}phone {c |}{col 25}{res}{space 2} .1473588{col 37}{space 2}   .05616{col 48}{space 1}    2.62{col 57}{space 3}0.009{col 65}{space 4} .0372871{col 78}{space 3} .2574305
{txt}{space 12}electricity {c |}{col 25}{res}{space 2} .1293096{col 37}{space 2} .1035074{col 48}{space 1}    1.25{col 57}{space 3}0.212{col 65}{space 4}-.0735612{col 78}{space 3} .3321805
{txt}{space 16}wagejob {c |}{col 25}{res}{space 2} .0169294{col 37}{space 2} .0461459{col 48}{space 1}    0.37{col 57}{space 3}0.714{col 65}{space 4} -.073515{col 78}{space 3} .1073738
{txt}{space 13}enterprise {c |}{col 25}{res}{space 2} .2140972{col 37}{space 2} .0526316{col 48}{space 1}    4.07{col 57}{space 3}0.000{col 65}{space 4} .1109412{col 78}{space 3} .3172533
{txt}{space 10}weather_shock {c |}{col 25}{res}{space 2}  .130426{col 37}{space 2} .0358739{col 48}{space 1}    3.64{col 57}{space 3}0.000{col 65}{space 4} .0601145{col 78}{space 3} .2007376
{txt}{space 14}plot_area {c |}{col 25}{res}{space 2} .0031192{col 37}{space 2} .0013326{col 48}{space 1}    2.34{col 57}{space 3}0.019{col 65}{space 4} .0005073{col 78}{space 3} .0057311
{txt}{space 13}other_crop {c |}{col 25}{res}{space 2}-.0058777{col 37}{space 2} .0397716{col 48}{space 1}   -0.15{col 57}{space 3}0.883{col 65}{space 4}-.0838287{col 78}{space 3} .0720732
{txt}{space 10}motobike_mean {c |}{col 25}{res}{space 2} .3530031{col 37}{space 2} .1278794{col 48}{space 1}    2.76{col 57}{space 3}0.006{col 65}{space 4} .1023642{col 78}{space 3} .6036421
{txt}{space 13}phone_mean {c |}{col 25}{res}{space 2} .5201955{col 37}{space 2} .0813011{col 48}{space 1}    6.40{col 57}{space 3}0.000{col 65}{space 4} .3608483{col 78}{space 3} .6795428
{txt}{space 7}electricity_mean {c |}{col 25}{res}{space 2} .7766215{col 37}{space 2} .1333311{col 48}{space 1}    5.82{col 57}{space 3}0.000{col 65}{space 4} .5152972{col 78}{space 3} 1.037946
{txt}{space 11}wagejob_mean {c |}{col 25}{res}{space 2} .0393298{col 37}{space 2} .0744002{col 48}{space 1}    0.53{col 57}{space 3}0.597{col 65}{space 4} -.106492{col 78}{space 3} .1851515
{txt}{space 8}enterprise_mean {c |}{col 25}{res}{space 2} .1865708{col 37}{space 2} .0743971{col 48}{space 1}    2.51{col 57}{space 3}0.012{col 65}{space 4}  .040755{col 78}{space 3} .3323865
{txt}{space 14}pdd9_mean {c |}{col 25}{res}{space 2} .0104978{col 37}{space 2} .0255541{col 48}{space 1}    0.41{col 57}{space 3}0.681{col 65}{space 4}-.0395874{col 78}{space 3} .0605829
{txt}{space 17}year_2 {c |}{col 25}{res}{space 2} -.216024{col 37}{space 2} .0352212{col 48}{space 1}   -6.13{col 57}{space 3}0.000{col 65}{space 4}-.2850562{col 78}{space 3}-.1469918
{txt}{space 17}year_3 {c |}{col 25}{res}{space 2}-.1354934{col 37}{space 2}  .036243{col 48}{space 1}   -3.74{col 57}{space 3}0.000{col 65}{space 4}-.2065283{col 78}{space 3}-.0644584
{txt}{space 18}_cons {c |}{col 25}{res}{space 2} 4.672004{col 37}{space 2} .1246315{col 48}{space 1}   37.49{col 57}{space 3}0.000{col 65}{space 4}  4.42773{col 78}{space 3} 4.916277
{txt}{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                sigma_u {c |} {res} .89217853
                {txt}sigma_e {c |} {res} 1.2274622
                    {txt}rho {c |} {res} .34568167{txt}   (fraction of variance due to u_i)
{hline 24}{c BT}{hline 64}

{com}. eststo est7
{txt}
{com}. esttab using  S3.rtf, se replace star(* 0.1 ** 0.05 *** 0.01) cells (b(star fmt(%9.3f)) se (par(( )) fmt(%9.3f)))  stats(N r2_b  r2_w r2_o p, fmt(%4.0f %4.3f %4.3f %6.3f)) keep( pdd9 c.pdd9#c.dist_popcenter dist_popcenter $xlist  pdd9_mean _cons)
{res}{txt}(note: file S3.rtf not found)
(output written to {browse  `"S3.rtf"'})

{com}. restore
{txt}
{com}. 
. 
. 
. 
. 
. 
. ********************************************************************************  
. *                               Table S4                                       *
. ********************************************************************************
. preserve
{txt}
{com}. eststo clear
{txt}
{com}. drop if hdd9_own==.|hdd9_purchase==.
{txt}(7,192 observations deleted)

{com}. drop  pdd9_mean no_species_mean hhsize_mean dependent_share_mean head_age_mean female_head_mean head_read_mean motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean weather_shock_mean plot_area_mean other_crop_mean
{txt}
{com}. foreach x of varlist pdd9 hhsize dependent_share head_age female_head head_read  motobike phone  electricity wagejob enterprise weather_shock  plot_area other_crop{c -(}
{txt}  2{com}. egen `x'_mean=mean(`x'), by(HHID_panel)
{txt}  3{com}. {c )-}
{txt}
{com}. 
. eststo clear
{txt}
{com}. xtreg hdd9_own  pdd9   $xlist  pdd9_mean i.country i.year  , cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    82,550
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}    34,744

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0782                                         {txt}min = {res}         1
{txt}     between = {res}0.6105                                         {txt}avg = {res}       2.4
{txt}     overall = {res}0.5185                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}35{txt})     =  {res} 70956.84
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:34,744} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}        hdd9_own{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .2289411{col 30}{space 2} .0053368{col 41}{space 1}   42.90{col 50}{space 3}0.000{col 58}{space 4} .2184811{col 71}{space 3}  .239401
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0199893{col 30}{space 2} .0018284{col 41}{space 1}   10.93{col 50}{space 3}0.000{col 58}{space 4} .0164058{col 71}{space 3} .0235729
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0316314{col 30}{space 2} .0184609{col 41}{space 1}   -1.71{col 50}{space 3}0.087{col 58}{space 4}-.0678141{col 71}{space 3} .0045512
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0018132{col 30}{space 2} .0003194{col 41}{space 1}    5.68{col 50}{space 3}0.000{col 58}{space 4} .0011872{col 71}{space 3} .0024393
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0368507{col 30}{space 2} .0112429{col 41}{space 1}   -3.28{col 50}{space 3}0.001{col 58}{space 4}-.0588864{col 71}{space 3} -.014815
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0820646{col 30}{space 2} .0108273{col 41}{space 1}    7.58{col 50}{space 3}0.000{col 58}{space 4} .0608435{col 71}{space 3} .1032857
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}  .000432{col 30}{space 2} .0202187{col 41}{space 1}    0.02{col 50}{space 3}0.983{col 58}{space 4} -.039196{col 71}{space 3} .0400599
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0151645{col 30}{space 2} .0147642{col 41}{space 1}    1.03{col 50}{space 3}0.304{col 58}{space 4}-.0137728{col 71}{space 3} .0441018
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}-.0292366{col 30}{space 2} .0175851{col 41}{space 1}   -1.66{col 50}{space 3}0.096{col 58}{space 4}-.0637028{col 71}{space 3} .0052296
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}-.0711801{col 30}{space 2} .0140919{col 41}{space 1}   -5.05{col 50}{space 3}0.000{col 58}{space 4}-.0987997{col 71}{space 3}-.0435606
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .0074432{col 30}{space 2} .0139657{col 41}{space 1}    0.53{col 50}{space 3}0.594{col 58}{space 4}-.0199292{col 71}{space 3} .0348156
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0130409{col 30}{space 2}  .011313{col 41}{space 1}   -1.15{col 50}{space 3}0.249{col 58}{space 4}-.0352139{col 71}{space 3} .0091322
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0053113{col 30}{space 2} .0010791{col 41}{space 1}    4.92{col 50}{space 3}0.000{col 58}{space 4} .0031964{col 71}{space 3} .0074263
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1687443{col 30}{space 2} .0142739{col 41}{space 1}   11.82{col 50}{space 3}0.000{col 58}{space 4} .1407679{col 71}{space 3} .1967207
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0960305{col 30}{space 2} .0262241{col 41}{space 1}    3.66{col 50}{space 3}0.000{col 58}{space 4} .0446321{col 71}{space 3} .1474289
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .0165833{col 30}{space 2} .0206869{col 41}{space 1}    0.80{col 50}{space 3}0.423{col 58}{space 4}-.0239622{col 71}{space 3} .0571288
{txt}electricity_mean {c |}{col 18}{res}{space 2}-.1111915{col 30}{space 2} .0221938{col 41}{space 1}   -5.01{col 50}{space 3}0.000{col 58}{space 4}-.1546905{col 71}{space 3}-.0676924
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.1531674{col 30}{space 2} .0192232{col 41}{space 1}   -7.97{col 50}{space 3}0.000{col 58}{space 4}-.1908442{col 71}{space 3}-.1154905
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.2531462{col 30}{space 2}   .01811{col 41}{space 1}  -13.98{col 50}{space 3}0.000{col 58}{space 4}-.2886411{col 71}{space 3}-.2176514
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .2998333{col 30}{space 2} .0063445{col 41}{space 1}   47.26{col 50}{space 3}0.000{col 58}{space 4} .2873982{col 71}{space 3} .3122683
{txt}{space 16} {c |}
{space 9}country {c |}
{space 8}Nigeria  {c |}{col 18}{res}{space 2} .3496918{col 30}{space 2} .0198542{col 41}{space 1}   17.61{col 50}{space 3}0.000{col 58}{space 4} .3107782{col 71}{space 3} .3886054
{txt}{space 7}Ethiopia  {c |}{col 18}{res}{space 2}-.1162756{col 30}{space 2} .0208903{col 41}{space 1}   -5.57{col 50}{space 3}0.000{col 58}{space 4}-.1572199{col 71}{space 3}-.0753314
{txt}{space 9}Uganda  {c |}{col 18}{res}{space 2} .9876464{col 30}{space 2} .0217937{col 41}{space 1}   45.32{col 50}{space 3}0.000{col 58}{space 4} .9449316{col 71}{space 3} 1.030361
{txt}{space 7}Tanzania  {c |}{col 18}{res}{space 2} .5374965{col 30}{space 2} .0187986{col 41}{space 1}   28.59{col 50}{space 3}0.000{col 58}{space 4} .5006519{col 71}{space 3} .5743411
{txt}{space 9}Malawi  {c |}{col 18}{res}{space 2} .6413401{col 30}{space 2} .0256115{col 41}{space 1}   25.04{col 50}{space 3}0.000{col 58}{space 4} .5911425{col 71}{space 3} .6915376
{txt}{space 16} {c |}
{space 12}year {c |}
{space 11}2009  {c |}{col 18}{res}{space 2} -.243842{col 30}{space 2} .0324283{col 41}{space 1}   -7.52{col 50}{space 3}0.000{col 58}{space 4}-.3074004{col 71}{space 3}-.1802837
{txt}{space 11}2010  {c |}{col 18}{res}{space 2}-.0857712{col 30}{space 2} .0227618{col 41}{space 1}   -3.77{col 50}{space 3}0.000{col 58}{space 4}-.1303835{col 71}{space 3}-.0411588
{txt}{space 11}2011  {c |}{col 18}{res}{space 2}   .12744{col 30}{space 2} .0258958{col 41}{space 1}    4.92{col 50}{space 3}0.000{col 58}{space 4} .0766852{col 71}{space 3} .1781948
{txt}{space 11}2012  {c |}{col 18}{res}{space 2} .0123648{col 30}{space 2} .0227804{col 41}{space 1}    0.54{col 50}{space 3}0.587{col 58}{space 4}-.0322839{col 71}{space 3} .0570135
{txt}{space 11}2013  {c |}{col 18}{res}{space 2} .0815978{col 30}{space 2} .0267822{col 41}{space 1}    3.05{col 50}{space 3}0.002{col 58}{space 4} .0291058{col 71}{space 3} .1340899
{txt}{space 11}2014  {c |}{col 18}{res}{space 2}-.1557594{col 30}{space 2} .0246973{col 41}{space 1}   -6.31{col 50}{space 3}0.000{col 58}{space 4}-.2041652{col 71}{space 3}-.1073537
{txt}{space 11}2015  {c |}{col 18}{res}{space 2} .0708934{col 30}{space 2} .0249503{col 41}{space 1}    2.84{col 50}{space 3}0.004{col 58}{space 4} .0219917{col 71}{space 3}  .119795
{txt}{space 11}2016  {c |}{col 18}{res}{space 2}-.3353845{col 30}{space 2} .0348631{col 41}{space 1}   -9.62{col 50}{space 3}0.000{col 58}{space 4}-.4037149{col 71}{space 3}-.2670541
{txt}{space 11}2018  {c |}{col 18}{res}{space 2} .2965881{col 30}{space 2} .0269857{col 41}{space 1}   10.99{col 50}{space 3}0.000{col 58}{space 4} .2436972{col 71}{space 3}  .349479
{txt}{space 11}2019  {c |}{col 18}{res}{space 2}-.1455278{col 30}{space 2} .0277582{col 41}{space 1}   -5.24{col 50}{space 3}0.000{col 58}{space 4}-.1999329{col 71}{space 3}-.0911227
{txt}{space 16} {c |}
{space 11}_cons {c |}{col 18}{res}{space 2}-.1881102{col 30}{space 2} .0339461{col 41}{space 1}   -5.54{col 50}{space 3}0.000{col 58}{space 4}-.2546432{col 71}{space 3}-.1215771
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .41007338
         {txt}sigma_e {c |} {res} 1.0171168
             {txt}rho {c |} {res} .13982041{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est1
{txt}
{com}. 
. 
. xtreg hdd9_own  pdd9   $xlist  pdd9_mean $year_ETHIOPIA if country==3, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    10,583
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     5,088

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0275                                         {txt}min = {res}         1
{txt}     between = {res}0.6382                                         {txt}avg = {res}       2.1
{txt}     overall = {res}0.5168                                         {txt}max = {res}         3

                                                {txt}Wald chi2({res}21{txt})     =  {res} 10582.84
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:5,088} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}        hdd9_own{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .0725307{col 30}{space 2} .0109034{col 41}{space 1}    6.65{col 50}{space 3}0.000{col 58}{space 4} .0511604{col 71}{space 3}  .093901
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}  .029883{col 30}{space 2} .0054403{col 41}{space 1}    5.49{col 50}{space 3}0.000{col 58}{space 4} .0192203{col 71}{space 3} .0405457
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0198742{col 30}{space 2} .0403712{col 41}{space 1}   -0.49{col 50}{space 3}0.623{col 58}{space 4}-.0990002{col 71}{space 3} .0592519
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0019179{col 30}{space 2} .0006944{col 41}{space 1}    2.76{col 50}{space 3}0.006{col 58}{space 4}  .000557{col 71}{space 3} .0032788
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0661727{col 30}{space 2} .0230801{col 41}{space 1}   -2.87{col 50}{space 3}0.004{col 58}{space 4}-.1114089{col 71}{space 3}-.0209365
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0925665{col 30}{space 2} .0240914{col 41}{space 1}    3.84{col 50}{space 3}0.000{col 58}{space 4} .0453482{col 71}{space 3} .1397848
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}-.1470962{col 30}{space 2} .1247508{col 41}{space 1}   -1.18{col 50}{space 3}0.238{col 58}{space 4}-.3916034{col 71}{space 3}  .097411
{txt}{space 11}phone {c |}{col 18}{res}{space 2}  .024182{col 30}{space 2} .0349653{col 41}{space 1}    0.69{col 50}{space 3}0.489{col 58}{space 4}-.0443487{col 71}{space 3} .0927127
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}-.1526929{col 30}{space 2} .0409561{col 41}{space 1}   -3.73{col 50}{space 3}0.000{col 58}{space 4}-.2329653{col 71}{space 3}-.0724204
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}-.0158386{col 30}{space 2} .0339591{col 41}{space 1}   -0.47{col 50}{space 3}0.641{col 58}{space 4}-.0823971{col 71}{space 3}   .05072
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}-.0222789{col 30}{space 2} .0405573{col 41}{space 1}   -0.55{col 50}{space 3}0.583{col 58}{space 4}-.1017698{col 71}{space 3} .0572121
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1410461{col 30}{space 2} .0261434{col 41}{space 1}   -5.40{col 50}{space 3}0.000{col 58}{space 4}-.1922862{col 71}{space 3} -.089806
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0195358{col 30}{space 2}  .006519{col 41}{space 1}    3.00{col 50}{space 3}0.003{col 58}{space 4} .0067588{col 71}{space 3} .0323129
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.0194398{col 30}{space 2} .0276761{col 41}{space 1}   -0.70{col 50}{space 3}0.482{col 58}{space 4}-.0736839{col 71}{space 3} .0348042
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1873364{col 30}{space 2}  .171457{col 41}{space 1}    1.09{col 50}{space 3}0.275{col 58}{space 4}-.1487131{col 71}{space 3} .5233859
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}-.0795805{col 30}{space 2} .0475415{col 41}{space 1}   -1.67{col 50}{space 3}0.094{col 58}{space 4}-.1727601{col 71}{space 3} .0135992
{txt}electricity_mean {c |}{col 18}{res}{space 2}-.2213507{col 30}{space 2} .0540766{col 41}{space 1}   -4.09{col 50}{space 3}0.000{col 58}{space 4}-.3273389{col 71}{space 3}-.1153624
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.2066598{col 30}{space 2} .0461313{col 41}{space 1}   -4.48{col 50}{space 3}0.000{col 58}{space 4}-.2970755{col 71}{space 3} -.116244
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.1966504{col 30}{space 2} .0484207{col 41}{space 1}   -4.06{col 50}{space 3}0.000{col 58}{space 4}-.2915533{col 71}{space 3}-.1017475
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .2792311{col 30}{space 2} .0130262{col 41}{space 1}   21.44{col 50}{space 3}0.000{col 58}{space 4} .2537002{col 71}{space 3} .3047621
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}-.1285239{col 30}{space 2}  .016266{col 41}{space 1}   -7.90{col 50}{space 3}0.000{col 58}{space 4}-.1604046{col 71}{space 3}-.0966432
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .4724241{col 30}{space 2} .0491895{col 41}{space 1}    9.60{col 50}{space 3}0.000{col 58}{space 4} .3760146{col 71}{space 3} .5688337
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .42273203
         {txt}sigma_e {c |} {res} .80682908
             {txt}rho {c |} {res} .21538826{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est2
{txt}
{com}. 
. xtreg hdd9_own  pdd9   $xlist  pdd9_mean $year_MALAWI if country==6, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     9,155
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     3,447

{txt}R-sq:                                           Obs per group:
     within  = {res}0.1662                                         {txt}min = {res}         1
{txt}     between = {res}0.5607                                         {txt}avg = {res}       2.7
{txt}     overall = {res}0.4503                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}22{txt})     =  {res}  7010.28
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,447} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}        hdd9_own{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .3173126{col 30}{space 2} .0133082{col 41}{space 1}   23.84{col 50}{space 3}0.000{col 58}{space 4}  .291229{col 71}{space 3} .3433962
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0027509{col 30}{space 2} .0071995{col 41}{space 1}   -0.38{col 50}{space 3}0.702{col 58}{space 4}-.0168617{col 71}{space 3} .0113599
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0287026{col 30}{space 2} .0572435{col 41}{space 1}   -0.50{col 50}{space 3}0.616{col 58}{space 4}-.1408979{col 71}{space 3} .0834926
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0029858{col 30}{space 2} .0010369{col 41}{space 1}    2.88{col 50}{space 3}0.004{col 58}{space 4} .0009535{col 71}{space 3} .0050181
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} -.067816{col 30}{space 2} .0332682{col 41}{space 1}   -2.04{col 50}{space 3}0.042{col 58}{space 4}-.1330205{col 71}{space 3}-.0026116
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0585542{col 30}{space 2} .0359559{col 41}{space 1}    1.63{col 50}{space 3}0.103{col 58}{space 4}-.0119181{col 71}{space 3} .1290266
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2289414{col 30}{space 2} .1251567{col 41}{space 1}    1.83{col 50}{space 3}0.067{col 58}{space 4}-.0163612{col 71}{space 3}  .474244
{txt}{space 11}phone {c |}{col 18}{res}{space 2}  .008772{col 30}{space 2} .0419425{col 41}{space 1}    0.21{col 50}{space 3}0.834{col 58}{space 4}-.0734339{col 71}{space 3} .0909779
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}-.0624507{col 30}{space 2} .0632369{col 41}{space 1}   -0.99{col 50}{space 3}0.323{col 58}{space 4}-.1863927{col 71}{space 3} .0614913
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}-.0851474{col 30}{space 2} .0452934{col 41}{space 1}   -1.88{col 50}{space 3}0.060{col 58}{space 4}-.1739208{col 71}{space 3} .0036259
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .0524232{col 30}{space 2} .0369344{col 41}{space 1}    1.42{col 50}{space 3}0.156{col 58}{space 4}-.0199669{col 71}{space 3} .1248132
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1033078{col 30}{space 2} .0275902{col 41}{space 1}   -3.74{col 50}{space 3}0.000{col 58}{space 4}-.1573836{col 71}{space 3} -.049232
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .1462866{col 30}{space 2} .0294973{col 41}{space 1}    4.96{col 50}{space 3}0.000{col 58}{space 4} .0884729{col 71}{space 3} .2041002
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1652043{col 30}{space 2} .0430404{col 41}{space 1}    3.84{col 50}{space 3}0.000{col 58}{space 4} .0808466{col 71}{space 3}  .249562
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}-.1289342{col 30}{space 2} .1777006{col 41}{space 1}   -0.73{col 50}{space 3}0.468{col 58}{space 4} -.477221{col 71}{space 3} .2193527
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}-.0335231{col 30}{space 2} .0604924{col 41}{space 1}   -0.55{col 50}{space 3}0.579{col 58}{space 4}-.1520861{col 71}{space 3} .0850398
{txt}electricity_mean {c |}{col 18}{res}{space 2}-.0033553{col 30}{space 2} .0771947{col 41}{space 1}   -0.04{col 50}{space 3}0.965{col 58}{space 4}-.1546541{col 71}{space 3} .1479435
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.0230671{col 30}{space 2} .0617441{col 41}{space 1}   -0.37{col 50}{space 3}0.709{col 58}{space 4}-.1440833{col 71}{space 3} .0979491
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.2235382{col 30}{space 2} .0532937{col 41}{space 1}   -4.19{col 50}{space 3}0.000{col 58}{space 4}-.3279921{col 71}{space 3}-.1190844
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .2721752{col 30}{space 2} .0174642{col 41}{space 1}   15.58{col 50}{space 3}0.000{col 58}{space 4}  .237946{col 71}{space 3} .3064044
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2} .5630036{col 30}{space 2} .0350039{col 41}{space 1}   16.08{col 50}{space 3}0.000{col 58}{space 4} .4943971{col 71}{space 3}   .63161
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .2735095{col 30}{space 2} .0285378{col 41}{space 1}    9.58{col 50}{space 3}0.000{col 58}{space 4} .2175763{col 71}{space 3} .3294426
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .0144419{col 30}{space 2} .0664906{col 41}{space 1}    0.22{col 50}{space 3}0.828{col 58}{space 4}-.1158773{col 71}{space 3}  .144761
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .39556837
         {txt}sigma_e {c |} {res} 1.0803198
             {txt}rho {c |} {res} .11822185{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est3
{txt}
{com}. 
. xtreg hdd9_own  pdd9   $xlist  pdd9_mean $year_NIGER if country==1, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     7,044
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     4,069

{txt}R-sq:                                           Obs per group:
     within  = {res}0.1557                                         {txt}min = {res}         1
{txt}     between = {res}0.4767                                         {txt}avg = {res}       1.7
{txt}     overall = {res}0.4049                                         {txt}max = {res}         2

                                                {txt}Wald chi2({res}21{txt})     =  {res}  4771.79
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:4,069} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}        hdd9_own{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .1973853{col 30}{space 2} .0219255{col 41}{space 1}    9.00{col 50}{space 3}0.000{col 58}{space 4} .1544121{col 71}{space 3} .2403586
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0000582{col 30}{space 2} .0035628{col 41}{space 1}   -0.02{col 50}{space 3}0.987{col 58}{space 4}-.0070411{col 71}{space 3} .0069248
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0136811{col 30}{space 2} .0477215{col 41}{space 1}   -0.29{col 50}{space 3}0.774{col 58}{space 4}-.1072136{col 71}{space 3} .0798513
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} -.001344{col 30}{space 2}  .000783{col 41}{space 1}   -1.72{col 50}{space 3}0.086{col 58}{space 4}-.0028786{col 71}{space 3} .0001906
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.1293763{col 30}{space 2} .0256726{col 41}{space 1}   -5.04{col 50}{space 3}0.000{col 58}{space 4}-.1796937{col 71}{space 3} -.079059
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0596942{col 30}{space 2} .0243584{col 41}{space 1}    2.45{col 50}{space 3}0.014{col 58}{space 4} .0119526{col 71}{space 3} .1074359
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0346525{col 30}{space 2} .0431278{col 41}{space 1}    0.80{col 50}{space 3}0.422{col 58}{space 4}-.0498765{col 71}{space 3} .1191815
{txt}{space 11}phone {c |}{col 18}{res}{space 2}-.1009946{col 30}{space 2}  .040821{col 41}{space 1}   -2.47{col 50}{space 3}0.013{col 58}{space 4}-.1810023{col 71}{space 3}-.0209869
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1047576{col 30}{space 2} .0399843{col 41}{space 1}    2.62{col 50}{space 3}0.009{col 58}{space 4} .0263899{col 71}{space 3} .1831253
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1021303{col 30}{space 2} .0434451{col 41}{space 1}    2.35{col 50}{space 3}0.019{col 58}{space 4} .0169795{col 71}{space 3}  .187281
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}-.0031368{col 30}{space 2} .0377983{col 41}{space 1}   -0.08{col 50}{space 3}0.934{col 58}{space 4}  -.07722{col 71}{space 3} .0709465
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} -.003441{col 30}{space 2}  .028432{col 41}{space 1}   -0.12{col 50}{space 3}0.904{col 58}{space 4}-.0591668{col 71}{space 3} .0522847
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0006563{col 30}{space 2} .0011029{col 41}{space 1}    0.60{col 50}{space 3}0.552{col 58}{space 4}-.0015053{col 71}{space 3} .0028179
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .3706267{col 30}{space 2} .1470621{col 41}{space 1}    2.52{col 50}{space 3}0.012{col 58}{space 4} .0823904{col 71}{space 3}  .658863
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}-.0753269{col 30}{space 2} .0525013{col 41}{space 1}   -1.43{col 50}{space 3}0.151{col 58}{space 4}-.1782275{col 71}{space 3} .0275737
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}-.0638446{col 30}{space 2} .0509537{col 41}{space 1}   -1.25{col 50}{space 3}0.210{col 58}{space 4}-.1637119{col 71}{space 3} .0360228
{txt}electricity_mean {c |}{col 18}{res}{space 2} -.237074{col 30}{space 2} .0504786{col 41}{space 1}   -4.70{col 50}{space 3}0.000{col 58}{space 4}-.3360102{col 71}{space 3}-.1381379
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.1731654{col 30}{space 2} .0494818{col 41}{space 1}   -3.50{col 50}{space 3}0.000{col 58}{space 4} -.270148{col 71}{space 3}-.0761828
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.0647682{col 30}{space 2} .0460524{col 41}{space 1}   -1.41{col 50}{space 3}0.160{col 58}{space 4}-.1550292{col 71}{space 3} .0254928
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .2307013{col 30}{space 2}  .023388{col 41}{space 1}    9.86{col 50}{space 3}0.000{col 58}{space 4} .1848617{col 71}{space 3}  .276541
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2}  .323043{col 30}{space 2} .0191127{col 41}{space 1}   16.90{col 50}{space 3}0.000{col 58}{space 4} .2855827{col 71}{space 3} .3605033
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .1166266{col 30}{space 2} .0555234{col 41}{space 1}    2.10{col 50}{space 3}0.036{col 58}{space 4} .0078026{col 71}{space 3} .2254505
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .25712132
         {txt}sigma_e {c |} {res} .76186721
             {txt}rho {c |} {res} .10225205{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est4
{txt}
{com}. 
. 
. xtreg hdd9_own  pdd9   $xlist  pdd9_mean $year_NIGERIA if country==2, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    18,429
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     8,218

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0993                                         {txt}min = {res}         1
{txt}     between = {res}0.4545                                         {txt}avg = {res}       2.2
{txt}     overall = {res}0.4045                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}23{txt})     =  {res} 11082.69
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:8,218} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}        hdd9_own{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2}  .232078{col 30}{space 2}  .011813{col 41}{space 1}   19.65{col 50}{space 3}0.000{col 58}{space 4}  .208925{col 71}{space 3}  .255231
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}  .010716{col 30}{space 2} .0029827{col 41}{space 1}    3.59{col 50}{space 3}0.000{col 58}{space 4}   .00487{col 71}{space 3}  .016562
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0363237{col 30}{space 2} .0317138{col 41}{space 1}   -1.15{col 50}{space 3}0.252{col 58}{space 4}-.0984816{col 71}{space 3} .0258341
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0007506{col 30}{space 2} .0005705{col 41}{space 1}    1.32{col 50}{space 3}0.188{col 58}{space 4}-.0003676{col 71}{space 3} .0018688
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0428719{col 30}{space 2} .0228444{col 41}{space 1}   -1.88{col 50}{space 3}0.061{col 58}{space 4}-.0876462{col 71}{space 3} .0019024
{txt}{space 7}head_read {c |}{col 18}{res}{space 2}-.0261416{col 30}{space 2} .0193083{col 41}{space 1}   -1.35{col 50}{space 3}0.176{col 58}{space 4}-.0639851{col 71}{space 3} .0117019
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}-.0533326{col 30}{space 2} .0267002{col 41}{space 1}   -2.00{col 50}{space 3}0.046{col 58}{space 4} -.105664{col 71}{space 3}-.0010012
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0543923{col 30}{space 2} .0265015{col 41}{space 1}    2.05{col 50}{space 3}0.040{col 58}{space 4} .0024502{col 71}{space 3} .1063343
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}-.0047538{col 30}{space 2} .0323875{col 41}{space 1}   -0.15{col 50}{space 3}0.883{col 58}{space 4} -.068232{col 71}{space 3} .0587245
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0025082{col 30}{space 2} .0293049{col 41}{space 1}    0.09{col 50}{space 3}0.932{col 58}{space 4}-.0549282{col 71}{space 3} .0599447
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .0223209{col 30}{space 2} .0279333{col 41}{space 1}    0.80{col 50}{space 3}0.424{col 58}{space 4}-.0324273{col 71}{space 3}  .077069
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} .1046307{col 30}{space 2} .0363266{col 41}{space 1}    2.88{col 50}{space 3}0.004{col 58}{space 4} .0334319{col 71}{space 3} .1758296
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0158071{col 30}{space 2} .0074746{col 41}{space 1}    2.11{col 50}{space 3}0.034{col 58}{space 4} .0011572{col 71}{space 3} .0304569
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1640597{col 30}{space 2} .0461682{col 41}{space 1}    3.55{col 50}{space 3}0.000{col 58}{space 4} .0735718{col 71}{space 3} .2545476
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .2228397{col 30}{space 2} .0367329{col 41}{space 1}    6.07{col 50}{space 3}0.000{col 58}{space 4} .1508446{col 71}{space 3} .2948348
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .0725493{col 30}{space 2} .0393678{col 41}{space 1}    1.84{col 50}{space 3}0.065{col 58}{space 4}-.0046102{col 71}{space 3} .1497088
{txt}electricity_mean {c |}{col 18}{res}{space 2}-.2989324{col 30}{space 2}  .040759{col 41}{space 1}   -7.33{col 50}{space 3}0.000{col 58}{space 4}-.3788186{col 71}{space 3}-.2190462
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.1977187{col 30}{space 2} .0386889{col 41}{space 1}   -5.11{col 50}{space 3}0.000{col 58}{space 4}-.2735474{col 71}{space 3}-.1218899
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.1885144{col 30}{space 2} .0352227{col 41}{space 1}   -5.35{col 50}{space 3}0.000{col 58}{space 4}-.2575496{col 71}{space 3}-.1194792
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .2117643{col 30}{space 2} .0137466{col 41}{space 1}   15.40{col 50}{space 3}0.000{col 58}{space 4} .1848214{col 71}{space 3} .2387072
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.5233821{col 30}{space 2}  .022234{col 41}{space 1}  -23.54{col 50}{space 3}0.000{col 58}{space 4}  -.56696{col 71}{space 3}-.4798043
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2}-.2997497{col 30}{space 2} .0219591{col 41}{space 1}  -13.65{col 50}{space 3}0.000{col 58}{space 4}-.3427887{col 71}{space 3}-.2567106
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2}-.3180665{col 30}{space 2} .0222853{col 41}{space 1}  -14.27{col 50}{space 3}0.000{col 58}{space 4}-.3617449{col 71}{space 3}-.2743882
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .7727287{col 30}{space 2} .0459978{col 41}{space 1}   16.80{col 50}{space 3}0.000{col 58}{space 4} .6825747{col 71}{space 3} .8628826
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .55143368
         {txt}sigma_e {c |} {res} .85452267
             {txt}rho {c |} {res} .29399845{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est5
{txt}
{com}. 
. 
. xtreg hdd9_own  pdd9   $xlist  pdd9_mean $year_TANZANIA if country==5, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    17,046
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     8,817

{txt}R-sq:                                           Obs per group:
     within  = {res}0.1105                                         {txt}min = {res}         1
{txt}     between = {res}0.6556                                         {txt}avg = {res}       1.9
{txt}     overall = {res}0.5796                                         {txt}max = {res}         5

                                                {txt}Wald chi2({res}23{txt})     =  {res} 20814.27
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:8,817} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}        hdd9_own{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .2953455{col 30}{space 2} .0120988{col 41}{space 1}   24.41{col 50}{space 3}0.000{col 58}{space 4} .2716323{col 71}{space 3} .3190587
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0266378{col 30}{space 2} .0041994{col 41}{space 1}    6.34{col 50}{space 3}0.000{col 58}{space 4} .0184071{col 71}{space 3} .0348686
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0440803{col 30}{space 2} .0418239{col 41}{space 1}   -1.05{col 50}{space 3}0.292{col 58}{space 4}-.1260537{col 71}{space 3}  .037893
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0020322{col 30}{space 2} .0007099{col 41}{space 1}   -2.86{col 50}{space 3}0.004{col 58}{space 4}-.0034237{col 71}{space 3}-.0006408
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0622128{col 30}{space 2}  .022594{col 41}{space 1}   -2.75{col 50}{space 3}0.006{col 58}{space 4}-.1064963{col 71}{space 3}-.0179293
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0332891{col 30}{space 2} .0260734{col 41}{space 1}    1.28{col 50}{space 3}0.202{col 58}{space 4}-.0178138{col 71}{space 3}  .084392
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0668397{col 30}{space 2} .0549528{col 41}{space 1}    1.22{col 50}{space 3}0.224{col 58}{space 4}-.0408657{col 71}{space 3} .1745451
{txt}{space 11}phone {c |}{col 18}{res}{space 2}-.0506504{col 30}{space 2} .0370027{col 41}{space 1}   -1.37{col 50}{space 3}0.171{col 58}{space 4}-.1231743{col 71}{space 3} .0218735
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}-.1555193{col 30}{space 2} .0435875{col 41}{space 1}   -3.57{col 50}{space 3}0.000{col 58}{space 4}-.2409493{col 71}{space 3}-.0700893
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} -.023113{col 30}{space 2} .0280287{col 41}{space 1}   -0.82{col 50}{space 3}0.410{col 58}{space 4}-.0780483{col 71}{space 3} .0318223
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .0155198{col 30}{space 2} .0290792{col 41}{space 1}    0.53{col 50}{space 3}0.594{col 58}{space 4}-.0414743{col 71}{space 3} .0725139
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0790391{col 30}{space 2} .0234674{col 41}{space 1}   -3.37{col 50}{space 3}0.001{col 58}{space 4}-.1250344{col 71}{space 3}-.0330438
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0156232{col 30}{space 2} .0048243{col 41}{space 1}    3.24{col 50}{space 3}0.001{col 58}{space 4} .0061679{col 71}{space 3} .0250786
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .2188395{col 30}{space 2} .0292999{col 41}{space 1}    7.47{col 50}{space 3}0.000{col 58}{space 4} .1614126{col 71}{space 3} .2762663
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}-.0012141{col 30}{space 2} .0660368{col 41}{space 1}   -0.02{col 50}{space 3}0.985{col 58}{space 4}-.1306438{col 71}{space 3} .1282156
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}-.0890016{col 30}{space 2} .0484716{col 41}{space 1}   -1.84{col 50}{space 3}0.066{col 58}{space 4}-.1840042{col 71}{space 3}  .006001
{txt}electricity_mean {c |}{col 18}{res}{space 2} .0276333{col 30}{space 2} .0508055{col 41}{space 1}    0.54{col 50}{space 3}0.587{col 58}{space 4}-.0719436{col 71}{space 3} .1272103
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.2015791{col 30}{space 2}  .037325{col 41}{space 1}   -5.40{col 50}{space 3}0.000{col 58}{space 4}-.2747348{col 71}{space 3}-.1284234
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.2641617{col 30}{space 2} .0376173{col 41}{space 1}   -7.02{col 50}{space 3}0.000{col 58}{space 4}-.3378902{col 71}{space 3}-.1904332
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .2623017{col 30}{space 2} .0134133{col 41}{space 1}   19.56{col 50}{space 3}0.000{col 58}{space 4} .2360121{col 71}{space 3} .2885914
{txt}{space 10}year_1 {c |}{col 18}{res}{space 2} .0514387{col 30}{space 2} .0246591{col 41}{space 1}    2.09{col 50}{space 3}0.037{col 58}{space 4} .0031077{col 71}{space 3} .0997697
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2} .0307463{col 30}{space 2} .0203743{col 41}{space 1}    1.51{col 50}{space 3}0.131{col 58}{space 4}-.0091865{col 71}{space 3} .0706791
{txt}{space 10}year_7 {c |}{col 18}{res}{space 2} -.002136{col 30}{space 2} .0226813{col 41}{space 1}   -0.09{col 50}{space 3}0.925{col 58}{space 4}-.0465907{col 71}{space 3} .0423186
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .4826065{col 30}{space 2} .0539877{col 41}{space 1}    8.94{col 50}{space 3}0.000{col 58}{space 4} .3767926{col 71}{space 3} .5884205
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .44195664
         {txt}sigma_e {c |} {res} .99908067
             {txt}rho {c |} {res} .16365954{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est6
{txt}
{com}. 
. 
. xtreg hdd9_own  pdd9   $xlist  pdd9_mean  $year_UGANDA if country==4, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    20,293
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     5,105

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0727                                         {txt}min = {res}         1
{txt}     between = {res}0.6607                                         {txt}avg = {res}       4.0
{txt}     overall = {res}0.4725                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}25{txt})     =  {res} 17543.40
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:5,105} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}        hdd9_own{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .2260514{col 30}{space 2} .0104819{col 41}{space 1}   21.57{col 50}{space 3}0.000{col 58}{space 4} .2055072{col 71}{space 3} .2465956
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0328326{col 30}{space 2} .0045105{col 41}{space 1}    7.28{col 50}{space 3}0.000{col 58}{space 4} .0239922{col 71}{space 3}  .041673
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0413164{col 30}{space 2}  .046077{col 41}{space 1}   -0.90{col 50}{space 3}0.370{col 58}{space 4}-.1316258{col 71}{space 3} .0489929
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}  .002846{col 30}{space 2} .0008116{col 41}{space 1}    3.51{col 50}{space 3}0.000{col 58}{space 4} .0012553{col 71}{space 3} .0044367
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0129076{col 30}{space 2} .0257692{col 41}{space 1}   -0.50{col 50}{space 3}0.616{col 58}{space 4}-.0634143{col 71}{space 3} .0375991
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .1699218{col 30}{space 2} .0264035{col 41}{space 1}    6.44{col 50}{space 3}0.000{col 58}{space 4} .1181719{col 71}{space 3} .2216716
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0143539{col 30}{space 2} .0457923{col 41}{space 1}    0.31{col 50}{space 3}0.754{col 58}{space 4}-.0753974{col 71}{space 3} .1041052
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1096989{col 30}{space 2} .0311658{col 41}{space 1}    3.52{col 50}{space 3}0.000{col 58}{space 4}  .048615{col 71}{space 3} .1707828
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}  .069206{col 30}{space 2} .0305109{col 41}{space 1}    2.27{col 50}{space 3}0.023{col 58}{space 4} .0094058{col 71}{space 3} .1290063
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}-.1693952{col 30}{space 2} .0246971{col 41}{space 1}   -6.86{col 50}{space 3}0.000{col 58}{space 4}-.2178005{col 71}{space 3}-.1209898
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}-.0262687{col 30}{space 2} .0280844{col 41}{space 1}   -0.94{col 50}{space 3}0.350{col 58}{space 4} -.081313{col 71}{space 3} .0287756
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0224151{col 30}{space 2} .0226847{col 41}{space 1}   -0.99{col 50}{space 3}0.323{col 58}{space 4}-.0668763{col 71}{space 3} .0220462
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0036948{col 30}{space 2} .0019723{col 41}{space 1}    1.87{col 50}{space 3}0.061{col 58}{space 4}-.0001708{col 71}{space 3} .0075603
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1950911{col 30}{space 2} .0252482{col 41}{space 1}    7.73{col 50}{space 3}0.000{col 58}{space 4} .1456056{col 71}{space 3} .2445766
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0685499{col 30}{space 2} .0671226{col 41}{space 1}    1.02{col 50}{space 3}0.307{col 58}{space 4} -.063008{col 71}{space 3} .2001078
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .0160592{col 30}{space 2} .0520765{col 41}{space 1}    0.31{col 50}{space 3}0.758{col 58}{space 4}-.0860088{col 71}{space 3} .1181272
{txt}electricity_mean {c |}{col 18}{res}{space 2}-.1092212{col 30}{space 2} .0514522{col 41}{space 1}   -2.12{col 50}{space 3}0.034{col 58}{space 4}-.2100657{col 71}{space 3}-.0083767
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.1803489{col 30}{space 2} .0429307{col 41}{space 1}   -4.20{col 50}{space 3}0.000{col 58}{space 4}-.2644915{col 71}{space 3}-.0962064
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.3467825{col 30}{space 2}   .04381{col 41}{space 1}   -7.92{col 50}{space 3}0.000{col 58}{space 4}-.4326485{col 71}{space 3}-.2609165
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .4590369{col 30}{space 2} .0137037{col 41}{space 1}   33.50{col 50}{space 3}0.000{col 58}{space 4} .4321782{col 71}{space 3} .4858956
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.0946885{col 30}{space 2} .0280405{col 41}{space 1}   -3.38{col 50}{space 3}0.001{col 58}{space 4}-.1496469{col 71}{space 3}-.0397301
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2} .1218857{col 30}{space 2} .0281883{col 41}{space 1}    4.32{col 50}{space 3}0.000{col 58}{space 4} .0666376{col 71}{space 3} .1771339
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}  .357557{col 30}{space 2} .0275492{col 41}{space 1}   12.98{col 50}{space 3}0.000{col 58}{space 4} .3035614{col 71}{space 3} .4115525
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2} .2216119{col 30}{space 2} .0268278{col 41}{space 1}    8.26{col 50}{space 3}0.000{col 58}{space 4} .1690304{col 71}{space 3} .2741934
{txt}{space 9}year_10 {c |}{col 18}{res}{space 2} .3173685{col 30}{space 2} .0266506{col 41}{space 1}   11.91{col 50}{space 3}0.000{col 58}{space 4} .2651343{col 71}{space 3} .3696027
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .0526347{col 30}{space 2} .0642385{col 41}{space 1}    0.82{col 50}{space 3}0.413{col 58}{space 4}-.0732706{col 71}{space 3} .1785399
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .54500537
         {txt}sigma_e {c |} {res} 1.1715101
             {txt}rho {c |} {res}  .1779196{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est7
{txt}
{com}. esttab using  S4.rtf, se replace star(* 0.1 ** 0.05 *** 0.01) cells (b(star fmt(%9.3f)) se (par(( )) fmt(%9.3f)))  stats(N r2_b  r2_w r2_o p, fmt(%4.0f %4.3f %4.3f %6.3f)) keep(pdd9   $xlist  pdd9_mean _cons)
{res}{txt}(note: file S4.rtf not found)
(output written to {browse  `"S4.rtf"'})

{com}. 
. 
. 
. 
. 
. ********************************************************************************  
. *                               Table S5                                       *
. ********************************************************************************
. eststo clear
{txt}
{com}. xtreg hdd9_purchase  pdd9   $xlist  pdd9_mean i.country i.year  , cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    82,550
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}    34,744

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0283                                         {txt}min = {res}         1
{txt}     between = {res}0.4949                                         {txt}avg = {res}       2.4
{txt}     overall = {res}0.4217                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}35{txt})     =  {res} 45211.41
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:34,744} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}   hdd9_purchase{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .0039823{col 30}{space 2} .0063817{col 41}{space 1}    0.62{col 50}{space 3}0.533{col 58}{space 4}-.0085256{col 71}{space 3} .0164901
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0011206{col 30}{space 2} .0027949{col 41}{space 1}    0.40{col 50}{space 3}0.688{col 58}{space 4}-.0043574{col 71}{space 3} .0065986
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0361638{col 30}{space 2} .0290758{col 41}{space 1}   -1.24{col 50}{space 3}0.214{col 58}{space 4}-.0931512{col 71}{space 3} .0208236
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0038962{col 30}{space 2}  .000509{col 41}{space 1}   -7.65{col 50}{space 3}0.000{col 58}{space 4}-.0048939{col 71}{space 3}-.0028985
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0167018{col 30}{space 2} .0176895{col 41}{space 1}    0.94{col 50}{space 3}0.345{col 58}{space 4} -.017969{col 71}{space 3} .0513725
{txt}{space 7}head_read {c |}{col 18}{res}{space 2}  .295018{col 30}{space 2} .0157294{col 41}{space 1}   18.76{col 50}{space 3}0.000{col 58}{space 4}  .264189{col 71}{space 3} .3258471
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1239685{col 30}{space 2} .0289665{col 41}{space 1}    4.28{col 50}{space 3}0.000{col 58}{space 4} .0671952{col 71}{space 3} .1807417
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2649609{col 30}{space 2} .0200931{col 41}{space 1}   13.19{col 50}{space 3}0.000{col 58}{space 4} .2255791{col 71}{space 3} .3043428
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .2663456{col 30}{space 2} .0240881{col 41}{space 1}   11.06{col 50}{space 3}0.000{col 58}{space 4} .2191339{col 71}{space 3} .3135574
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2150796{col 30}{space 2} .0193795{col 41}{space 1}   11.10{col 50}{space 3}0.000{col 58}{space 4} .1770964{col 71}{space 3} .2530628
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2902488{col 30}{space 2} .0187777{col 41}{space 1}   15.46{col 50}{space 3}0.000{col 58}{space 4} .2534452{col 71}{space 3} .3270525
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0495975{col 30}{space 2} .0152594{col 41}{space 1}   -3.25{col 50}{space 3}0.001{col 58}{space 4}-.0795054{col 71}{space 3}-.0196897
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0011953{col 30}{space 2} .0012324{col 41}{space 1}   -0.97{col 50}{space 3}0.332{col 58}{space 4}-.0036108{col 71}{space 3} .0012202
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.0367639{col 30}{space 2} .0184072{col 41}{space 1}   -2.00{col 50}{space 3}0.046{col 58}{space 4}-.0728414{col 71}{space 3}-.0006865
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0411037{col 30}{space 2} .0398198{col 41}{space 1}    1.03{col 50}{space 3}0.302{col 58}{space 4}-.0369417{col 71}{space 3} .1191492
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .6645476{col 30}{space 2} .0300037{col 41}{space 1}   22.15{col 50}{space 3}0.000{col 58}{space 4} .6057413{col 71}{space 3} .7233538
{txt}electricity_mean {c |}{col 18}{res}{space 2}  .814626{col 30}{space 2} .0328596{col 41}{space 1}   24.79{col 50}{space 3}0.000{col 58}{space 4} .7502223{col 71}{space 3} .8790297
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .3505039{col 30}{space 2} .0293255{col 41}{space 1}   11.95{col 50}{space 3}0.000{col 58}{space 4}  .293027{col 71}{space 3} .4079808
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .4580629{col 30}{space 2} .0267057{col 41}{space 1}   17.15{col 50}{space 3}0.000{col 58}{space 4} .4057207{col 71}{space 3} .5104052
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} -.248023{col 30}{space 2} .0082945{col 41}{space 1}  -29.90{col 50}{space 3}0.000{col 58}{space 4}  -.26428{col 71}{space 3} -.231766
{txt}{space 16} {c |}
{space 9}country {c |}
{space 8}Nigeria  {c |}{col 18}{res}{space 2}-.7083755{col 30}{space 2} .0336388{col 41}{space 1}  -21.06{col 50}{space 3}0.000{col 58}{space 4}-.7743062{col 71}{space 3}-.6424447
{txt}{space 7}Ethiopia  {c |}{col 18}{res}{space 2}-1.905325{col 30}{space 2} .0341543{col 41}{space 1}  -55.79{col 50}{space 3}0.000{col 58}{space 4}-1.972266{col 71}{space 3}-1.838384
{txt}{space 9}Uganda  {c |}{col 18}{res}{space 2}-1.344389{col 30}{space 2} .0346999{col 41}{space 1}  -38.74{col 50}{space 3}0.000{col 58}{space 4}-1.412399{col 71}{space 3}-1.276378
{txt}{space 7}Tanzania  {c |}{col 18}{res}{space 2}-.8451787{col 30}{space 2} .0329501{col 41}{space 1}  -25.65{col 50}{space 3}0.000{col 58}{space 4}-.9097597{col 71}{space 3}-.7805976
{txt}{space 9}Malawi  {c |}{col 18}{res}{space 2} -.161006{col 30}{space 2} .0412185{col 41}{space 1}   -3.91{col 50}{space 3}0.000{col 58}{space 4}-.2417927{col 71}{space 3}-.0802192
{txt}{space 16} {c |}
{space 12}year {c |}
{space 11}2009  {c |}{col 18}{res}{space 2}-.1644622{col 30}{space 2} .0431813{col 41}{space 1}   -3.81{col 50}{space 3}0.000{col 58}{space 4}-.2490959{col 71}{space 3}-.0798285
{txt}{space 11}2010  {c |}{col 18}{res}{space 2}-.0023028{col 30}{space 2} .0306318{col 41}{space 1}   -0.08{col 50}{space 3}0.940{col 58}{space 4}-.0623401{col 71}{space 3} .0577346
{txt}{space 11}2011  {c |}{col 18}{res}{space 2}-.0654856{col 30}{space 2} .0359749{col 41}{space 1}   -1.82{col 50}{space 3}0.069{col 58}{space 4} -.135995{col 71}{space 3} .0050239
{txt}{space 11}2012  {c |}{col 18}{res}{space 2} -.036667{col 30}{space 2} .0309902{col 41}{space 1}   -1.18{col 50}{space 3}0.237{col 58}{space 4}-.0974067{col 71}{space 3} .0240727
{txt}{space 11}2013  {c |}{col 18}{res}{space 2} .1102496{col 30}{space 2} .0363537{col 41}{space 1}    3.03{col 50}{space 3}0.002{col 58}{space 4} .0389977{col 71}{space 3} .1815016
{txt}{space 11}2014  {c |}{col 18}{res}{space 2}-.0319152{col 30}{space 2} .0360631{col 41}{space 1}   -0.88{col 50}{space 3}0.376{col 58}{space 4}-.1025977{col 71}{space 3} .0387672
{txt}{space 11}2015  {c |}{col 18}{res}{space 2} .2154467{col 30}{space 2} .0345638{col 41}{space 1}    6.23{col 50}{space 3}0.000{col 58}{space 4} .1477029{col 71}{space 3} .2831905
{txt}{space 11}2016  {c |}{col 18}{res}{space 2} .1338088{col 30}{space 2} .0488965{col 41}{space 1}    2.74{col 50}{space 3}0.006{col 58}{space 4} .0379733{col 71}{space 3} .2296442
{txt}{space 11}2018  {c |}{col 18}{res}{space 2}  .274568{col 30}{space 2}  .037372{col 41}{space 1}    7.35{col 50}{space 3}0.000{col 58}{space 4} .2013201{col 71}{space 3} .3478158
{txt}{space 11}2019  {c |}{col 18}{res}{space 2} .1881666{col 30}{space 2} .0380428{col 41}{space 1}    4.95{col 50}{space 3}0.000{col 58}{space 4} .1136041{col 71}{space 3} .2627291
{txt}{space 16} {c |}
{space 11}_cons {c |}{col 18}{res}{space 2} 4.461853{col 30}{space 2} .0532222{col 41}{space 1}   83.83{col 50}{space 3}0.000{col 58}{space 4}  4.35754{col 71}{space 3} 4.566167
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .98471562
         {txt}sigma_e {c |} {res} 1.3909744
             {txt}rho {c |} {res} .33385206{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est1
{txt}
{com}. 
. 
. xtreg hdd9_purchase  pdd9   $xlist  pdd9_mean $year_ETHIOPIA if country==3, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    10,583
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     5,088

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0329                                         {txt}min = {res}         1
{txt}     between = {res}0.5607                                         {txt}avg = {res}       2.1
{txt}     overall = {res}0.4766                                         {txt}max = {res}         3

                                                {txt}Wald chi2({res}21{txt})     =  {res}  7204.91
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:5,088} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}   hdd9_purchase{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .0288698{col 30}{space 2} .0130466{col 41}{space 1}    2.21{col 50}{space 3}0.027{col 58}{space 4}  .003299{col 71}{space 3} .0544406
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0343251{col 30}{space 2} .0083259{col 41}{space 1}    4.12{col 50}{space 3}0.000{col 58}{space 4} .0180067{col 71}{space 3} .0506435
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0074607{col 30}{space 2} .0660029{col 41}{space 1}   -0.11{col 50}{space 3}0.910{col 58}{space 4}-.1368239{col 71}{space 3} .1219026
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0049179{col 30}{space 2} .0011278{col 41}{space 1}   -4.36{col 50}{space 3}0.000{col 58}{space 4}-.0071285{col 71}{space 3}-.0027074
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0080696{col 30}{space 2} .0394135{col 41}{space 1}   -0.20{col 50}{space 3}0.838{col 58}{space 4}-.0853187{col 71}{space 3} .0691794
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3376892{col 30}{space 2} .0357286{col 41}{space 1}    9.45{col 50}{space 3}0.000{col 58}{space 4} .2676624{col 71}{space 3}  .407716
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}  .052808{col 30}{space 2} .1716289{col 41}{space 1}    0.31{col 50}{space 3}0.758{col 58}{space 4}-.2835784{col 71}{space 3} .3891944
{txt}{space 11}phone {c |}{col 18}{res}{space 2}   .20484{col 30}{space 2} .0445754{col 41}{space 1}    4.60{col 50}{space 3}0.000{col 58}{space 4} .1174738{col 71}{space 3} .2922061
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .4047418{col 30}{space 2} .0542589{col 41}{space 1}    7.46{col 50}{space 3}0.000{col 58}{space 4} .2983964{col 71}{space 3} .5110873
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}-.0617334{col 30}{space 2} .0645079{col 41}{space 1}   -0.96{col 50}{space 3}0.339{col 58}{space 4}-.1881665{col 71}{space 3} .0646998
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .3012055{col 30}{space 2} .0608703{col 41}{space 1}    4.95{col 50}{space 3}0.000{col 58}{space 4} .1819018{col 71}{space 3} .4205091
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1294374{col 30}{space 2}  .035026{col 41}{space 1}   -3.70{col 50}{space 3}0.000{col 58}{space 4} -.198087{col 71}{space 3}-.0607878
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} -.012986{col 30}{space 2} .0057751{col 41}{space 1}   -2.25{col 50}{space 3}0.025{col 58}{space 4} -.024305{col 71}{space 3} -.001667
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .2340699{col 30}{space 2} .0371021{col 41}{space 1}    6.31{col 50}{space 3}0.000{col 58}{space 4} .1613511{col 71}{space 3} .3067888
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .6972608{col 30}{space 2} .2569264{col 41}{space 1}    2.71{col 50}{space 3}0.007{col 58}{space 4} .1936943{col 71}{space 3} 1.200827
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .6672631{col 30}{space 2} .0674285{col 41}{space 1}    9.90{col 50}{space 3}0.000{col 58}{space 4} .5351056{col 71}{space 3} .7994206
{txt}electricity_mean {c |}{col 18}{res}{space 2}  .859345{col 30}{space 2} .0795023{col 41}{space 1}   10.81{col 50}{space 3}0.000{col 58}{space 4} .7035233{col 71}{space 3} 1.015167
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .7876162{col 30}{space 2} .0941898{col 41}{space 1}    8.36{col 50}{space 3}0.000{col 58}{space 4} .6030075{col 71}{space 3} .9722249
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .3486485{col 30}{space 2} .0750383{col 41}{space 1}    4.65{col 50}{space 3}0.000{col 58}{space 4} .2015761{col 71}{space 3} .4957209
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.2021654{col 30}{space 2} .0172347{col 41}{space 1}  -11.73{col 50}{space 3}0.000{col 58}{space 4}-.2359448{col 71}{space 3} -.168386
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}-.2297235{col 30}{space 2} .0245453{col 41}{space 1}   -9.36{col 50}{space 3}0.000{col 58}{space 4}-.2778314{col 71}{space 3}-.1816157
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 2.304581{col 30}{space 2} .0849323{col 41}{space 1}   27.13{col 50}{space 3}0.000{col 58}{space 4} 2.138117{col 71}{space 3} 2.471045
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .92124527
         {txt}sigma_e {c |} {res} 1.1082993
             {txt}rho {c |} {res}  .4086108{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est2
{txt}
{com}. 
. xtreg hdd9_purchase  pdd9   $xlist  pdd9_mean $year_MALAWI if country==6, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     9,155
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     3,447

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0488                                         {txt}min = {res}         1
{txt}     between = {res}0.5059                                         {txt}avg = {res}       2.7
{txt}     overall = {res}0.4315                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}22{txt})     =  {res}  5461.59
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,447} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}   hdd9_purchase{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2}-.0122859{col 30}{space 2} .0169108{col 41}{space 1}   -0.73{col 50}{space 3}0.468{col 58}{space 4}-.0454304{col 71}{space 3} .0208585
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0171889{col 30}{space 2} .0101529{col 41}{space 1}    1.69{col 50}{space 3}0.090{col 58}{space 4}-.0027103{col 71}{space 3} .0370882
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.4055607{col 30}{space 2} .0859136{col 41}{space 1}   -4.72{col 50}{space 3}0.000{col 58}{space 4}-.5739483{col 71}{space 3} -.237173
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0072105{col 30}{space 2} .0015781{col 41}{space 1}   -4.57{col 50}{space 3}0.000{col 58}{space 4}-.0103036{col 71}{space 3}-.0041174
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.1293879{col 30}{space 2}  .050701{col 41}{space 1}   -2.55{col 50}{space 3}0.011{col 58}{space 4}  -.22876{col 71}{space 3}-.0300158
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3041983{col 30}{space 2} .0516055{col 41}{space 1}    5.89{col 50}{space 3}0.000{col 58}{space 4} .2030534{col 71}{space 3} .4053431
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2183675{col 30}{space 2} .1458771{col 41}{space 1}    1.50{col 50}{space 3}0.134{col 58}{space 4}-.0675464{col 71}{space 3} .5042814
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .4297851{col 30}{space 2} .0604734{col 41}{space 1}    7.11{col 50}{space 3}0.000{col 58}{space 4} .3112593{col 71}{space 3} .5483108
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .5304345{col 30}{space 2} .0962794{col 41}{space 1}    5.51{col 50}{space 3}0.000{col 58}{space 4} .3417304{col 71}{space 3} .7191385
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}  .317736{col 30}{space 2} .0649298{col 41}{space 1}    4.89{col 50}{space 3}0.000{col 58}{space 4} .1904759{col 71}{space 3} .4449961
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .3672773{col 30}{space 2} .0490494{col 41}{space 1}    7.49{col 50}{space 3}0.000{col 58}{space 4} .2711423{col 71}{space 3} .4634124
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0942493{col 30}{space 2} .0387118{col 41}{space 1}   -2.43{col 50}{space 3}0.015{col 58}{space 4}-.1701231{col 71}{space 3}-.0183755
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0104369{col 30}{space 2}  .029444{col 41}{space 1}   -0.35{col 50}{space 3}0.723{col 58}{space 4}-.0681462{col 71}{space 3} .0472723
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} -.005101{col 30}{space 2} .0572654{col 41}{space 1}   -0.09{col 50}{space 3}0.929{col 58}{space 4}-.1173391{col 71}{space 3}  .107137
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .4603734{col 30}{space 2} .2375913{col 41}{space 1}    1.94{col 50}{space 3}0.053{col 58}{space 4} -.005297{col 71}{space 3} .9260439
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .5400978{col 30}{space 2} .0920042{col 41}{space 1}    5.87{col 50}{space 3}0.000{col 58}{space 4} .3597729{col 71}{space 3} .7204227
{txt}electricity_mean {c |}{col 18}{res}{space 2} .9049092{col 30}{space 2} .1273068{col 41}{space 1}    7.11{col 50}{space 3}0.000{col 58}{space 4} .6553925{col 71}{space 3} 1.154426
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}  .548971{col 30}{space 2} .0940249{col 41}{space 1}    5.84{col 50}{space 3}0.000{col 58}{space 4} .3646856{col 71}{space 3} .7332563
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .6750612{col 30}{space 2} .0822026{col 41}{space 1}    8.21{col 50}{space 3}0.000{col 58}{space 4}  .513947{col 71}{space 3} .8361753
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.2472667{col 30}{space 2} .0249932{col 41}{space 1}   -9.89{col 50}{space 3}0.000{col 58}{space 4}-.2962524{col 71}{space 3}-.1982809
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.2317679{col 30}{space 2} .0489227{col 41}{space 1}   -4.74{col 50}{space 3}0.000{col 58}{space 4}-.3276547{col 71}{space 3}-.1358812
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} -.011183{col 30}{space 2} .0400627{col 41}{space 1}   -0.28{col 50}{space 3}0.780{col 58}{space 4}-.0897045{col 71}{space 3} .0673385
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.476926{col 30}{space 2} .1088903{col 41}{space 1}   41.11{col 50}{space 3}0.000{col 58}{space 4} 4.263505{col 71}{space 3} 4.690347
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .94760357
         {txt}sigma_e {c |} {res}  1.489792
             {txt}rho {c |} {res} .28804231{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est3
{txt}
{com}. 
. xtreg hdd9_purchase  pdd9   $xlist  pdd9_mean $year_NIGER if country==1, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     7,044
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     4,069

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0217                                         {txt}min = {res}         1
{txt}     between = {res}0.3097                                         {txt}avg = {res}       1.7
{txt}     overall = {res}0.2440                                         {txt}max = {res}         2

                                                {txt}Wald chi2({res}21{txt})     =  {res}  2323.27
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:4,069} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}   hdd9_purchase{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .2281132{col 30}{space 2} .0378599{col 41}{space 1}    6.03{col 50}{space 3}0.000{col 58}{space 4} .1539092{col 71}{space 3} .3023173
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0167356{col 30}{space 2} .0072052{col 41}{space 1}    2.32{col 50}{space 3}0.020{col 58}{space 4} .0026136{col 71}{space 3} .0308576
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0782751{col 30}{space 2} .1071147{col 41}{space 1}   -0.73{col 50}{space 3}0.465{col 58}{space 4}-.2882161{col 71}{space 3} .1316658
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0008318{col 30}{space 2} .0015999{col 41}{space 1}    0.52{col 50}{space 3}0.603{col 58}{space 4}-.0023039{col 71}{space 3} .0039676
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0882308{col 30}{space 2} .0636703{col 41}{space 1}    1.39{col 50}{space 3}0.166{col 58}{space 4}-.0365607{col 71}{space 3} .2130224
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3640223{col 30}{space 2} .0482295{col 41}{space 1}    7.55{col 50}{space 3}0.000{col 58}{space 4} .2694943{col 71}{space 3} .4585503
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2332104{col 30}{space 2} .0998436{col 41}{space 1}    2.34{col 50}{space 3}0.020{col 58}{space 4} .0375205{col 71}{space 3} .4289003
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1478941{col 30}{space 2} .0814572{col 41}{space 1}    1.82{col 50}{space 3}0.069{col 58}{space 4} -.011759{col 71}{space 3} .3075473
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}  .224841{col 30}{space 2} .1089059{col 41}{space 1}    2.06{col 50}{space 3}0.039{col 58}{space 4} .0113893{col 71}{space 3} .4382927
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2835598{col 30}{space 2} .0890238{col 41}{space 1}    3.19{col 50}{space 3}0.001{col 58}{space 4} .1090764{col 71}{space 3} .4580433
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}-.1737196{col 30}{space 2} .0722002{col 41}{space 1}   -2.41{col 50}{space 3}0.016{col 58}{space 4}-.3152295{col 71}{space 3}-.0322098
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1465092{col 30}{space 2} .0502486{col 41}{space 1}   -2.92{col 50}{space 3}0.004{col 58}{space 4}-.2449946{col 71}{space 3}-.0480237
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0005281{col 30}{space 2} .0016676{col 41}{space 1}   -0.32{col 50}{space 3}0.751{col 58}{space 4}-.0037966{col 71}{space 3} .0027403
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0697816{col 30}{space 2} .2433595{col 41}{space 1}    0.29{col 50}{space 3}0.774{col 58}{space 4}-.4071943{col 71}{space 3} .5467576
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1456749{col 30}{space 2} .1251222{col 41}{space 1}    1.16{col 50}{space 3}0.244{col 58}{space 4}-.0995601{col 71}{space 3} .3909098
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .4665053{col 30}{space 2}  .101602{col 41}{space 1}    4.59{col 50}{space 3}0.000{col 58}{space 4}  .267369{col 71}{space 3} .6656416
{txt}electricity_mean {c |}{col 18}{res}{space 2} .6709489{col 30}{space 2} .1296436{col 41}{space 1}    5.18{col 50}{space 3}0.000{col 58}{space 4}  .416852{col 71}{space 3} .9250457
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .2765942{col 30}{space 2} .1123867{col 41}{space 1}    2.46{col 50}{space 3}0.014{col 58}{space 4} .0563203{col 71}{space 3} .4968682
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .5980706{col 30}{space 2} .0894371{col 41}{space 1}    6.69{col 50}{space 3}0.000{col 58}{space 4} .4227772{col 71}{space 3}  .773364
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.3293337{col 30}{space 2} .0433456{col 41}{space 1}   -7.60{col 50}{space 3}0.000{col 58}{space 4}-.4142895{col 71}{space 3}-.2443779
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2} .0191601{col 30}{space 2} .0396751{col 41}{space 1}    0.48{col 50}{space 3}0.629{col 58}{space 4}-.0586018{col 71}{space 3} .0969219
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.218393{col 30}{space 2} .1175928{col 41}{space 1}   35.87{col 50}{space 3}0.000{col 58}{space 4} 3.987916{col 71}{space 3} 4.448871
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .72100716
         {txt}sigma_e {c |} {res} 1.5029883
             {txt}rho {c |} {res} .18707595{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est4
{txt}
{com}. 
. 
. xtreg hdd9_purchase  pdd9   $xlist  pdd9_mean $year_NIGERIA if country==2, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    18,429
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     8,218

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0223                                         {txt}min = {res}         1
{txt}     between = {res}0.3751                                         {txt}avg = {res}       2.2
{txt}     overall = {res}0.3244                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}23{txt})     =  {res}  6343.17
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:8,218} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}   hdd9_purchase{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .0154161{col 30}{space 2} .0159749{col 41}{space 1}    0.97{col 50}{space 3}0.335{col 58}{space 4}-.0158942{col 71}{space 3} .0467264
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0088861{col 30}{space 2} .0049866{col 41}{space 1}   -1.78{col 50}{space 3}0.075{col 58}{space 4}-.0186597{col 71}{space 3} .0008874
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0758525{col 30}{space 2} .0552353{col 41}{space 1}    1.37{col 50}{space 3}0.170{col 58}{space 4}-.0324067{col 71}{space 3} .1841118
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0007798{col 30}{space 2} .0010176{col 41}{space 1}    0.77{col 50}{space 3}0.443{col 58}{space 4}-.0012146{col 71}{space 3} .0027742
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .2144079{col 30}{space 2} .0403716{col 41}{space 1}    5.31{col 50}{space 3}0.000{col 58}{space 4}  .135281{col 71}{space 3} .2935349
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2663009{col 30}{space 2}  .030417{col 41}{space 1}    8.76{col 50}{space 3}0.000{col 58}{space 4} .2066847{col 71}{space 3} .3259171
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0505892{col 30}{space 2}  .042032{col 41}{space 1}    1.20{col 50}{space 3}0.229{col 58}{space 4}-.0317919{col 71}{space 3} .1329704
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2243559{col 30}{space 2} .0422463{col 41}{space 1}    5.31{col 50}{space 3}0.000{col 58}{space 4} .1415546{col 71}{space 3} .3071572
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1335494{col 30}{space 2} .0497534{col 41}{space 1}    2.68{col 50}{space 3}0.007{col 58}{space 4} .0360345{col 71}{space 3} .2310644
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2284137{col 30}{space 2} .0530897{col 41}{space 1}    4.30{col 50}{space 3}0.000{col 58}{space 4} .1243598{col 71}{space 3} .3324676
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .3385972{col 30}{space 2}   .04379{col 41}{space 1}    7.73{col 50}{space 3}0.000{col 58}{space 4} .2527705{col 71}{space 3}  .424424
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0960612{col 30}{space 2} .0531849{col 41}{space 1}   -1.81{col 50}{space 3}0.071{col 58}{space 4}-.2003017{col 71}{space 3} .0081793
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0186462{col 30}{space 2} .0113527{col 41}{space 1}   -1.64{col 50}{space 3}0.100{col 58}{space 4} -.040897{col 71}{space 3} .0036046
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .2067037{col 30}{space 2} .0657966{col 41}{space 1}    3.14{col 50}{space 3}0.002{col 58}{space 4} .0777447{col 71}{space 3} .3356627
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}-.1222089{col 30}{space 2} .0584666{col 41}{space 1}   -2.09{col 50}{space 3}0.037{col 58}{space 4}-.2368013{col 71}{space 3}-.0076164
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .7794276{col 30}{space 2} .0644403{col 41}{space 1}   12.10{col 50}{space 3}0.000{col 58}{space 4} .6531268{col 71}{space 3} .9057283
{txt}electricity_mean {c |}{col 18}{res}{space 2} 1.042761{col 30}{space 2} .0640976{col 41}{space 1}   16.27{col 50}{space 3}0.000{col 58}{space 4} .9171315{col 71}{space 3}  1.16839
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .3703755{col 30}{space 2} .0701631{col 41}{space 1}    5.28{col 50}{space 3}0.000{col 58}{space 4} .2328584{col 71}{space 3} .5078926
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}  .133627{col 30}{space 2} .0573514{col 41}{space 1}    2.33{col 50}{space 3}0.020{col 58}{space 4} .0212203{col 71}{space 3} .2460338
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.1722757{col 30}{space 2} .0205091{col 41}{space 1}   -8.40{col 50}{space 3}0.000{col 58}{space 4}-.2124727{col 71}{space 3}-.1320787
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.2232765{col 30}{space 2} .0347917{col 41}{space 1}   -6.42{col 50}{space 3}0.000{col 58}{space 4}-.2914669{col 71}{space 3}-.1550861
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2}-.3088386{col 30}{space 2} .0344666{col 41}{space 1}   -8.96{col 50}{space 3}0.000{col 58}{space 4} -.376392{col 71}{space 3}-.2412852
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2}-.0575336{col 30}{space 2} .0343788{col 41}{space 1}   -1.67{col 50}{space 3}0.094{col 58}{space 4}-.1249148{col 71}{space 3} .0098475
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 3.745021{col 30}{space 2} .0820178{col 41}{space 1}   45.66{col 50}{space 3}0.000{col 58}{space 4} 3.584269{col 71}{space 3} 3.905773
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .95365027
         {txt}sigma_e {c |} {res} 1.3723453
             {txt}rho {c |} {res} .32564281{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est5
{txt}
{com}. 
. 
. xtreg hdd9_purchase  pdd9   $xlist  pdd9_mean $year_TANZANIA if country==5, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    17,046
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     8,817

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0191                                         {txt}min = {res}         1
{txt}     between = {res}0.4654                                         {txt}avg = {res}       1.9
{txt}     overall = {res}0.4274                                         {txt}max = {res}         5

                                                {txt}Wald chi2({res}23{txt})     =  {res}  9660.62
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:8,817} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}   hdd9_purchase{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2}-.0010869{col 30}{space 2} .0144521{col 41}{space 1}   -0.08{col 50}{space 3}0.940{col 58}{space 4}-.0294124{col 71}{space 3} .0272386
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0099436{col 30}{space 2} .0063163{col 41}{space 1}   -1.57{col 50}{space 3}0.115{col 58}{space 4}-.0223233{col 71}{space 3} .0024362
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0385898{col 30}{space 2} .0684059{col 41}{space 1}   -0.56{col 50}{space 3}0.573{col 58}{space 4} -.172663{col 71}{space 3} .0954833
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} -.002148{col 30}{space 2} .0011227{col 41}{space 1}   -1.91{col 50}{space 3}0.056{col 58}{space 4}-.0043485{col 71}{space 3} .0000525
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0588771{col 30}{space 2} .0366525{col 41}{space 1}    1.61{col 50}{space 3}0.108{col 58}{space 4}-.0129604{col 71}{space 3} .1307147
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .4303771{col 30}{space 2} .0382945{col 41}{space 1}   11.24{col 50}{space 3}0.000{col 58}{space 4} .3553214{col 71}{space 3} .5054329
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0776333{col 30}{space 2} .0775476{col 41}{space 1}    1.00{col 50}{space 3}0.317{col 58}{space 4}-.0743572{col 71}{space 3} .2296238
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .4007154{col 30}{space 2} .0471971{col 41}{space 1}    8.49{col 50}{space 3}0.000{col 58}{space 4} .3082108{col 71}{space 3}   .49322
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}  .098917{col 30}{space 2}   .06193{col 41}{space 1}    1.60{col 50}{space 3}0.110{col 58}{space 4}-.0224635{col 71}{space 3} .2202975
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2054413{col 30}{space 2} .0372556{col 41}{space 1}    5.51{col 50}{space 3}0.000{col 58}{space 4} .1324217{col 71}{space 3} .2784609
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}  .318705{col 30}{space 2} .0408313{col 41}{space 1}    7.81{col 50}{space 3}0.000{col 58}{space 4} .2386772{col 71}{space 3} .3987328
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0682691{col 30}{space 2} .0337579{col 41}{space 1}   -2.02{col 50}{space 3}0.043{col 58}{space 4}-.1344334{col 71}{space 3}-.0021047
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0064188{col 30}{space 2} .0043609{col 41}{space 1}   -1.47{col 50}{space 3}0.141{col 58}{space 4} -.014966{col 71}{space 3} .0021285
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.1093497{col 30}{space 2} .0365908{col 41}{space 1}   -2.99{col 50}{space 3}0.003{col 58}{space 4}-.1810664{col 71}{space 3}-.0376329
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .5525427{col 30}{space 2} .1011264{col 41}{space 1}    5.46{col 50}{space 3}0.000{col 58}{space 4} .3543386{col 71}{space 3} .7507468
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .6919189{col 30}{space 2} .0666437{col 41}{space 1}   10.38{col 50}{space 3}0.000{col 58}{space 4} .5612997{col 71}{space 3} .8225381
{txt}electricity_mean {c |}{col 18}{res}{space 2} .8087104{col 30}{space 2} .0771103{col 41}{space 1}   10.49{col 50}{space 3}0.000{col 58}{space 4}  .657577{col 71}{space 3} .9598439
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1999892{col 30}{space 2}  .054446{col 41}{space 1}    3.67{col 50}{space 3}0.000{col 58}{space 4}  .093277{col 71}{space 3} .3067014
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .5054748{col 30}{space 2} .0565759{col 41}{space 1}    8.93{col 50}{space 3}0.000{col 58}{space 4} .3945881{col 71}{space 3} .6163616
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.3103687{col 30}{space 2} .0173559{col 41}{space 1}  -17.88{col 50}{space 3}0.000{col 58}{space 4}-.3443856{col 71}{space 3}-.2763518
{txt}{space 10}year_1 {c |}{col 18}{res}{space 2}-.0047018{col 30}{space 2} .0334595{col 41}{space 1}   -0.14{col 50}{space 3}0.888{col 58}{space 4}-.0702813{col 71}{space 3} .0608777
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2}-.0412714{col 30}{space 2} .0286208{col 41}{space 1}   -1.44{col 50}{space 3}0.149{col 58}{space 4}-.0973671{col 71}{space 3} .0148243
{txt}{space 10}year_7 {c |}{col 18}{res}{space 2}-.0503713{col 30}{space 2} .0349371{col 41}{space 1}   -1.44{col 50}{space 3}0.149{col 58}{space 4}-.1188467{col 71}{space 3} .0181041
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 3.645053{col 30}{space 2} .0854022{col 41}{space 1}   42.68{col 50}{space 3}0.000{col 58}{space 4} 3.477668{col 71}{space 3} 3.812438
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} 1.0749284
         {txt}sigma_e {c |} {res} 1.3411357
             {txt}rho {c |} {res} .39113935{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est6
{txt}
{com}. 
. 
. xtreg hdd9_purchase  pdd9   $xlist  pdd9_mean  $year_UGANDA if country==4, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    20,293
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     5,105

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0377                                         {txt}min = {res}         1
{txt}     between = {res}0.4310                                         {txt}avg = {res}       4.0
{txt}     overall = {res}0.3084                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}25{txt})     =  {res}  4916.09
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:5,105} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}   hdd9_purchase{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} -.005009{col 30}{space 2} .0119508{col 41}{space 1}   -0.42{col 50}{space 3}0.675{col 58}{space 4}-.0284323{col 71}{space 3} .0184142
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0096666{col 30}{space 2} .0060922{col 41}{space 1}    1.59{col 50}{space 3}0.113{col 58}{space 4} -.002274{col 71}{space 3} .0216071
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0438789{col 30}{space 2} .0640744{col 41}{space 1}    0.68{col 50}{space 3}0.493{col 58}{space 4}-.0817045{col 71}{space 3} .1694624
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0068861{col 30}{space 2} .0012157{col 41}{space 1}   -5.66{col 50}{space 3}0.000{col 58}{space 4}-.0092689{col 71}{space 3}-.0045033
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}  .052448{col 30}{space 2} .0380617{col 41}{space 1}    1.38{col 50}{space 3}0.168{col 58}{space 4}-.0221515{col 71}{space 3} .1270476
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2260638{col 30}{space 2} .0348022{col 41}{space 1}    6.50{col 50}{space 3}0.000{col 58}{space 4} .1578527{col 71}{space 3} .2942749
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2641742{col 30}{space 2} .0579825{col 41}{space 1}    4.56{col 50}{space 3}0.000{col 58}{space 4} .1505306{col 71}{space 3} .3778177
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2844343{col 30}{space 2} .0379622{col 41}{space 1}    7.49{col 50}{space 3}0.000{col 58}{space 4} .2100297{col 71}{space 3} .3588389
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .4591086{col 30}{space 2} .0392584{col 41}{space 1}   11.69{col 50}{space 3}0.000{col 58}{space 4} .3821636{col 71}{space 3} .5360536
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1976331{col 30}{space 2} .0310657{col 41}{space 1}    6.36{col 50}{space 3}0.000{col 58}{space 4} .1367454{col 71}{space 3} .2585209
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2783542{col 30}{space 2} .0336193{col 41}{space 1}    8.28{col 50}{space 3}0.000{col 58}{space 4} .2124616{col 71}{space 3} .3442467
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} .0247614{col 30}{space 2}  .027121{col 41}{space 1}    0.91{col 50}{space 3}0.361{col 58}{space 4}-.0283948{col 71}{space 3} .0779177
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0003888{col 30}{space 2}  .001864{col 41}{space 1}    0.21{col 50}{space 3}0.835{col 58}{space 4}-.0032645{col 71}{space 3} .0040421
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.1238323{col 30}{space 2} .0325821{col 41}{space 1}   -3.80{col 50}{space 3}0.000{col 58}{space 4}-.1876919{col 71}{space 3}-.0599726
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1817586{col 30}{space 2} .0963568{col 41}{space 1}    1.89{col 50}{space 3}0.059{col 58}{space 4}-.0070973{col 71}{space 3} .3706145
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .5067038{col 30}{space 2} .0700418{col 41}{space 1}    7.23{col 50}{space 3}0.000{col 58}{space 4} .3694243{col 71}{space 3} .6439833
{txt}electricity_mean {c |}{col 18}{res}{space 2} .4959422{col 30}{space 2} .0757658{col 41}{space 1}    6.55{col 50}{space 3}0.000{col 58}{space 4}  .347444{col 71}{space 3} .6444404
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .4181632{col 30}{space 2}  .063041{col 41}{space 1}    6.63{col 50}{space 3}0.000{col 58}{space 4}  .294605{col 71}{space 3} .5417214
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .7719908{col 30}{space 2} .0612551{col 41}{space 1}   12.60{col 50}{space 3}0.000{col 58}{space 4} .6519329{col 71}{space 3} .8920486
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} -.273935{col 30}{space 2} .0179865{col 41}{space 1}  -15.23{col 50}{space 3}0.000{col 58}{space 4} -.309188{col 71}{space 3} -.238682
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.1576228{col 30}{space 2} .0352225{col 41}{space 1}   -4.48{col 50}{space 3}0.000{col 58}{space 4}-.2266576{col 71}{space 3} -.088588
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2} -.137737{col 30}{space 2} .0348587{col 41}{space 1}   -3.95{col 50}{space 3}0.000{col 58}{space 4}-.2060587{col 71}{space 3}-.0694153
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .2182982{col 30}{space 2} .0350614{col 41}{space 1}    6.23{col 50}{space 3}0.000{col 58}{space 4} .1495791{col 71}{space 3} .2870173
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2} .0266362{col 30}{space 2} .0348869{col 41}{space 1}    0.76{col 50}{space 3}0.445{col 58}{space 4}-.0417409{col 71}{space 3} .0950132
{txt}{space 9}year_10 {c |}{col 18}{res}{space 2}  .167045{col 30}{space 2}  .033402{col 41}{space 1}    5.00{col 50}{space 3}0.000{col 58}{space 4} .1015783{col 71}{space 3} .2325117
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 3.311555{col 30}{space 2} .0966084{col 41}{space 1}   34.28{col 50}{space 3}0.000{col 58}{space 4} 3.122206{col 71}{space 3} 3.500904
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} 1.0493206
         {txt}sigma_e {c |} {res} 1.4522365
             {txt}rho {c |} {res} .34300669{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est7
{txt}
{com}. 
. esttab using  S5.rtf, se replace star(* 0.1 ** 0.05 *** 0.01) cells (b(star fmt(%9.3f)) se (par(( )) fmt(%9.3f)))  stats(N r2_b  r2_w r2_o p, fmt(%4.0f %4.3f %4.3f %6.3f)) keep(pdd9   $xlist  pdd9_mean _cons)
{res}{txt}(note: file S5.rtf not found)
(output written to {browse  `"S5.rtf"'})

{com}. restore
{txt}
{com}. 
. 
. 
. 
. 
. ********************************************************************************
. *                                Table S6                                      *
. ********************************************************************************
. preserve
{txt}
{com}. drop if sum_vill<=1|sum_vill==.
{txt}(24,163 observations deleted)

{com}. 
. drop pdd9_mean no_species_mean hhsize_mean dependent_share_mean head_age_mean female_head_mean head_read_mean motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean weather_shock_mean plot_area_mean other_crop_mean
{txt}
{com}. egen pdd9_mean=mean(pdd9), by(HHID_panel)
{txt}
{com}. egen pdd9_mean_vill=mean(pdd9_vill), by(HHID_panel)
{txt}
{com}. egen pdd9_mean_town=mean(pdd9_town), by(HHID_panel)
{txt}
{com}. egen pdd9_mean_dist=mean(pdd9_dist), by(HHID_panel)
{txt}
{com}. 
. foreach x of varlist hhsize dependent_share head_age female_head head_read  motobike phone  electricity wagejob enterprise weather_shock  plot_area other_crop{c -(}
{txt}  2{com}. egen `x'_mean=mean(`x'), by(HHID_panel)
{txt}  3{com}. {c )-}
{txt}
{com}. 
. 
. *                                  hh_level                                    *
. eststo clear
{txt}
{com}. xtreg hdd9  pdd9   $xlist  pdd9_mean i.country i.year  , cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    65,579
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}    27,229

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0298                                         {txt}min = {res}         1
{txt}     between = {res}0.3642                                         {txt}avg = {res}       2.4
{txt}     overall = {res}0.2843                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}35{txt})     =  {res} 20480.98
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:27,229} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .1049413{col 30}{space 2} .0059733{col 41}{space 1}   17.57{col 50}{space 3}0.000{col 58}{space 4} .0932338{col 71}{space 3} .1166487
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} -.007599{col 30}{space 2} .0024818{col 41}{space 1}   -3.06{col 50}{space 3}0.002{col 58}{space 4}-.0124632{col 71}{space 3}-.0027349
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0471026{col 30}{space 2} .0276186{col 41}{space 1}    1.71{col 50}{space 3}0.088{col 58}{space 4}-.0070288{col 71}{space 3}  .101234
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0002698{col 30}{space 2}  .000465{col 41}{space 1}    0.58{col 50}{space 3}0.562{col 58}{space 4}-.0006416{col 71}{space 3} .0011812
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0699344{col 30}{space 2} .0169506{col 41}{space 1}    4.13{col 50}{space 3}0.000{col 58}{space 4} .0367118{col 71}{space 3} .1031569
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3054264{col 30}{space 2} .0147831{col 41}{space 1}   20.66{col 50}{space 3}0.000{col 58}{space 4}  .276452{col 71}{space 3} .3344008
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1195563{col 30}{space 2} .0293841{col 41}{space 1}    4.07{col 50}{space 3}0.000{col 58}{space 4} .0619646{col 71}{space 3} .1771481
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1690675{col 30}{space 2} .0192528{col 41}{space 1}    8.78{col 50}{space 3}0.000{col 58}{space 4} .1313326{col 71}{space 3} .2068024
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1509031{col 30}{space 2} .0227388{col 41}{space 1}    6.64{col 50}{space 3}0.000{col 58}{space 4} .1063359{col 71}{space 3} .1954703
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}  .127408{col 30}{space 2} .0198305{col 41}{space 1}    6.42{col 50}{space 3}0.000{col 58}{space 4}  .088541{col 71}{space 3} .1662751
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2082576{col 30}{space 2}  .018241{col 41}{space 1}   11.42{col 50}{space 3}0.000{col 58}{space 4}  .172506{col 71}{space 3} .2440092
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} -.069053{col 30}{space 2} .0142275{col 41}{space 1}   -4.85{col 50}{space 3}0.000{col 58}{space 4}-.0969385{col 71}{space 3}-.0411676
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0010025{col 30}{space 2} .0011243{col 41}{space 1}   -0.89{col 50}{space 3}0.373{col 58}{space 4} -.003206{col 71}{space 3}  .001201
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1214571{col 30}{space 2} .0162303{col 41}{space 1}    7.48{col 50}{space 3}0.000{col 58}{space 4} .0896462{col 71}{space 3} .1532679
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}  .041509{col 30}{space 2} .0397187{col 41}{space 1}    1.05{col 50}{space 3}0.296{col 58}{space 4}-.0363382{col 71}{space 3} .1193562
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}  .570139{col 30}{space 2} .0280369{col 41}{space 1}   20.34{col 50}{space 3}0.000{col 58}{space 4} .5151878{col 71}{space 3} .6250902
{txt}electricity_mean {c |}{col 18}{res}{space 2} .7014075{col 30}{space 2}  .031095{col 41}{space 1}   22.56{col 50}{space 3}0.000{col 58}{space 4} .6404625{col 71}{space 3} .7623526
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .2016277{col 30}{space 2} .0294769{col 41}{space 1}    6.84{col 50}{space 3}0.000{col 58}{space 4} .1438539{col 71}{space 3} .2594014
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .1698562{col 30}{space 2} .0255933{col 41}{space 1}    6.64{col 50}{space 3}0.000{col 58}{space 4} .1196942{col 71}{space 3} .2200183
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.0224813{col 30}{space 2} .0079096{col 41}{space 1}   -2.84{col 50}{space 3}0.004{col 58}{space 4}-.0379839{col 71}{space 3}-.0069786
{txt}{space 16} {c |}
{space 9}country {c |}
{space 8}Nigeria  {c |}{col 18}{res}{space 2}-.3748805{col 30}{space 2} .0320616{col 41}{space 1}  -11.69{col 50}{space 3}0.000{col 58}{space 4}-.4377201{col 71}{space 3} -.312041
{txt}{space 7}Ethiopia  {c |}{col 18}{res}{space 2}-1.505376{col 30}{space 2} .0312475{col 41}{space 1}  -48.18{col 50}{space 3}0.000{col 58}{space 4} -1.56662{col 71}{space 3}-1.444132
{txt}{space 9}Uganda  {c |}{col 18}{res}{space 2}-.4763147{col 30}{space 2} .0314446{col 41}{space 1}  -15.15{col 50}{space 3}0.000{col 58}{space 4} -.537945{col 71}{space 3}-.4146844
{txt}{space 7}Tanzania  {c |}{col 18}{res}{space 2}-.2621974{col 30}{space 2} .0313699{col 41}{space 1}   -8.36{col 50}{space 3}0.000{col 58}{space 4}-.3236813{col 71}{space 3}-.2007135
{txt}{space 9}Malawi  {c |}{col 18}{res}{space 2} .4473528{col 30}{space 2} .0408327{col 41}{space 1}   10.96{col 50}{space 3}0.000{col 58}{space 4} .3673221{col 71}{space 3} .5273835
{txt}{space 16} {c |}
{space 12}year {c |}
{space 11}2009  {c |}{col 18}{res}{space 2}-.2119596{col 30}{space 2} .0460785{col 41}{space 1}   -4.60{col 50}{space 3}0.000{col 58}{space 4}-.3022718{col 71}{space 3}-.1216475
{txt}{space 11}2010  {c |}{col 18}{res}{space 2} .0370795{col 30}{space 2} .0349394{col 41}{space 1}    1.06{col 50}{space 3}0.289{col 58}{space 4}-.0314005{col 71}{space 3} .1055595
{txt}{space 11}2011  {c |}{col 18}{res}{space 2} .0917951{col 30}{space 2} .0387084{col 41}{space 1}    2.37{col 50}{space 3}0.018{col 58}{space 4} .0159281{col 71}{space 3} .1676621
{txt}{space 11}2012  {c |}{col 18}{res}{space 2} .0461867{col 30}{space 2} .0354764{col 41}{space 1}    1.30{col 50}{space 3}0.193{col 58}{space 4}-.0233458{col 71}{space 3} .1157192
{txt}{space 11}2013  {c |}{col 18}{res}{space 2} .1282528{col 30}{space 2} .0389711{col 41}{space 1}    3.29{col 50}{space 3}0.001{col 58}{space 4} .0518708{col 71}{space 3} .2046348
{txt}{space 11}2014  {c |}{col 18}{res}{space 2}-.0501073{col 30}{space 2} .0392824{col 41}{space 1}   -1.28{col 50}{space 3}0.202{col 58}{space 4}-.1270995{col 71}{space 3} .0268849
{txt}{space 11}2015  {c |}{col 18}{res}{space 2} .1921556{col 30}{space 2} .0378514{col 41}{space 1}    5.08{col 50}{space 3}0.000{col 58}{space 4} .1179681{col 71}{space 3}  .266343
{txt}{space 11}2016  {c |}{col 18}{res}{space 2}-.1711942{col 30}{space 2} .0586205{col 41}{space 1}   -2.92{col 50}{space 3}0.003{col 58}{space 4}-.2860882{col 71}{space 3}-.0563002
{txt}{space 11}2018  {c |}{col 18}{res}{space 2} .4721261{col 30}{space 2} .0399222{col 41}{space 1}   11.83{col 50}{space 3}0.000{col 58}{space 4}   .39388{col 71}{space 3} .5503723
{txt}{space 11}2019  {c |}{col 18}{res}{space 2} .0124794{col 30}{space 2} .0388179{col 41}{space 1}    0.32{col 50}{space 3}0.748{col 58}{space 4}-.0636023{col 71}{space 3} .0885612
{txt}{space 16} {c |}
{space 11}_cons {c |}{col 18}{res}{space 2} 4.442334{col 30}{space 2} .0534638{col 41}{space 1}   83.09{col 50}{space 3}0.000{col 58}{space 4} 4.337547{col 71}{space 3} 4.547122
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .80391868
         {txt}sigma_e {c |} {res} 1.2322889
             {txt}rho {c |} {res} .29853977{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est1
{txt}
{com}. 
. xtreg hdd9  pdd9   $xlist  pdd9_mean $year_ETHIOPIA if country==3, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    11,410
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     4,555

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0224                                         {txt}min = {res}         1
{txt}     between = {res}0.3316                                         {txt}avg = {res}       2.5
{txt}     overall = {res}0.2218                                         {txt}max = {res}         3

                                                {txt}Wald chi2({res}21{txt})     =  {res}  2458.70
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:4,555} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .0539287{col 30}{space 2} .0110239{col 41}{space 1}    4.89{col 50}{space 3}0.000{col 58}{space 4} .0323223{col 71}{space 3} .0755351
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0309614{col 30}{space 2} .0072656{col 41}{space 1}    4.26{col 50}{space 3}0.000{col 58}{space 4} .0167211{col 71}{space 3} .0452018
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0466737{col 30}{space 2} .0571691{col 41}{space 1}   -0.82{col 50}{space 3}0.414{col 58}{space 4} -.158723{col 71}{space 3} .0653757
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0038514{col 30}{space 2} .0009949{col 41}{space 1}   -3.87{col 50}{space 3}0.000{col 58}{space 4}-.0058013{col 71}{space 3}-.0019014
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0028412{col 30}{space 2}  .036026{col 41}{space 1}   -0.08{col 50}{space 3}0.937{col 58}{space 4}-.0734508{col 71}{space 3} .0677685
{txt}{space 7}head_read {c |}{col 18}{res}{space 2}   .38516{col 30}{space 2} .0312284{col 41}{space 1}   12.33{col 50}{space 3}0.000{col 58}{space 4} .3239536{col 71}{space 3} .4463665
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}-.2271194{col 30}{space 2} .1577828{col 41}{space 1}   -1.44{col 50}{space 3}0.150{col 58}{space 4}-.5363681{col 71}{space 3} .0821293
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1805965{col 30}{space 2} .0377677{col 41}{space 1}    4.78{col 50}{space 3}0.000{col 58}{space 4} .1065732{col 71}{space 3} .2546197
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1561482{col 30}{space 2} .0461328{col 41}{space 1}    3.38{col 50}{space 3}0.001{col 58}{space 4} .0657295{col 71}{space 3} .2465669
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0873407{col 30}{space 2} .0633302{col 41}{space 1}    1.38{col 50}{space 3}0.168{col 58}{space 4}-.0367843{col 71}{space 3} .2114657
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2272176{col 30}{space 2} .0498917{col 41}{space 1}    4.55{col 50}{space 3}0.000{col 58}{space 4} .1294317{col 71}{space 3} .3250035
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}  -.14566{col 30}{space 2} .0293752{col 41}{space 1}   -4.96{col 50}{space 3}0.000{col 58}{space 4}-.2032344{col 71}{space 3}-.0880857
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0076979{col 30}{space 2} .0035577{col 41}{space 1}    2.16{col 50}{space 3}0.030{col 58}{space 4} .0007249{col 71}{space 3} .0146709
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .2120122{col 30}{space 2} .0311265{col 41}{space 1}    6.81{col 50}{space 3}0.000{col 58}{space 4} .1510054{col 71}{space 3} .2730191
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} 1.059095{col 30}{space 2} .2656293{col 41}{space 1}    3.99{col 50}{space 3}0.000{col 58}{space 4} .5384717{col 71}{space 3} 1.579719
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .4714012{col 30}{space 2} .0570747{col 41}{space 1}    8.26{col 50}{space 3}0.000{col 58}{space 4} .3595368{col 71}{space 3} .5832656
{txt}electricity_mean {c |}{col 18}{res}{space 2} .5146638{col 30}{space 2} .0678677{col 41}{space 1}    7.58{col 50}{space 3}0.000{col 58}{space 4} .3816456{col 71}{space 3}  .647682
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .4982624{col 30}{space 2} .0977845{col 41}{space 1}    5.10{col 50}{space 3}0.000{col 58}{space 4} .3066083{col 71}{space 3} .6899165
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .0978044{col 30}{space 2} .0635014{col 41}{space 1}    1.54{col 50}{space 3}0.124{col 58}{space 4}-.0266561{col 71}{space 3} .2222648
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .0492839{col 30}{space 2} .0148333{col 41}{space 1}    3.32{col 50}{space 3}0.001{col 58}{space 4} .0202111{col 71}{space 3} .0783567
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}-.1489418{col 30}{space 2} .0221739{col 41}{space 1}   -6.72{col 50}{space 3}0.000{col 58}{space 4}-.1924018{col 71}{space 3}-.1054817
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 3.138044{col 30}{space 2}  .071355{col 41}{space 1}   43.98{col 50}{space 3}0.000{col 58}{space 4} 2.998191{col 71}{space 3} 3.277897
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res}  .7322402
         {txt}sigma_e {c |} {res} 1.0763181
             {txt}rho {c |} {res} .31639574{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est2
{txt}
{com}. 
. xtreg hdd9  pdd9   $xlist  pdd9_mean $year_MALAWI if country==6, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     4,626
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     1,571

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0317                                         {txt}min = {res}         1
{txt}     between = {res}0.3927                                         {txt}avg = {res}       2.9
{txt}     overall = {res}0.2800                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}22{txt})     =  {res}  1538.67
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:1,571} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .1235523{col 30}{space 2} .0191692{col 41}{space 1}    6.45{col 50}{space 3}0.000{col 58}{space 4} .0859814{col 71}{space 3} .1611232
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0097393{col 30}{space 2} .0113092{col 41}{space 1}   -0.86{col 50}{space 3}0.389{col 58}{space 4}-.0319049{col 71}{space 3} .0124263
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} -.268054{col 30}{space 2} .1034015{col 41}{space 1}   -2.59{col 50}{space 3}0.010{col 58}{space 4}-.4707172{col 71}{space 3}-.0653908
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0023176{col 30}{space 2} .0017155{col 41}{space 1}   -1.35{col 50}{space 3}0.177{col 58}{space 4}-.0056799{col 71}{space 3} .0010447
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.1132922{col 30}{space 2} .0597651{col 41}{space 1}   -1.90{col 50}{space 3}0.058{col 58}{space 4}-.2304297{col 71}{space 3} .0038453
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2955717{col 30}{space 2} .0581609{col 41}{space 1}    5.08{col 50}{space 3}0.000{col 58}{space 4} .1815785{col 71}{space 3}  .409565
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2775657{col 30}{space 2} .1910768{col 41}{space 1}    1.45{col 50}{space 3}0.146{col 58}{space 4}-.0969379{col 71}{space 3} .6520694
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0970273{col 30}{space 2} .0693982{col 41}{space 1}    1.40{col 50}{space 3}0.162{col 58}{space 4}-.0389906{col 71}{space 3} .2330451
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .2106928{col 30}{space 2}  .139234{col 41}{space 1}    1.51{col 50}{space 3}0.130{col 58}{space 4}-.0622008{col 71}{space 3} .4835864
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1454629{col 30}{space 2} .0805816{col 41}{space 1}    1.81{col 50}{space 3}0.071{col 58}{space 4}-.0124742{col 71}{space 3}    .3034
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2402563{col 30}{space 2} .0558992{col 41}{space 1}    4.30{col 50}{space 3}0.000{col 58}{space 4} .1306959{col 71}{space 3} .3498168
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1657882{col 30}{space 2} .0439083{col 41}{space 1}   -3.78{col 50}{space 3}0.000{col 58}{space 4}-.2518469{col 71}{space 3}-.0797296
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0339784{col 30}{space 2} .0318202{col 41}{space 1}    1.07{col 50}{space 3}0.286{col 58}{space 4}-.0283881{col 71}{space 3}  .096345
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}  .035854{col 30}{space 2} .0613702{col 41}{space 1}    0.58{col 50}{space 3}0.559{col 58}{space 4}-.0844294{col 71}{space 3} .1561374
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} -.001975{col 30}{space 2} .3236041{col 41}{space 1}   -0.01{col 50}{space 3}0.995{col 58}{space 4}-.6362274{col 71}{space 3} .6322774
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .7479989{col 30}{space 2} .1079948{col 41}{space 1}    6.93{col 50}{space 3}0.000{col 58}{space 4}  .536333{col 71}{space 3} .9596648
{txt}electricity_mean {c |}{col 18}{res}{space 2} 1.009716{col 30}{space 2}  .176302{col 41}{space 1}    5.73{col 50}{space 3}0.000{col 58}{space 4} .6641703{col 71}{space 3} 1.355262
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .4037854{col 30}{space 2} .1147723{col 41}{space 1}    3.52{col 50}{space 3}0.000{col 58}{space 4} .1788358{col 71}{space 3} .6287349
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .3272637{col 30}{space 2}  .099458{col 41}{space 1}    3.29{col 50}{space 3}0.001{col 58}{space 4} .1323296{col 71}{space 3} .5221978
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.0265623{col 30}{space 2} .0292927{col 41}{space 1}   -0.91{col 50}{space 3}0.365{col 58}{space 4} -.083975{col 71}{space 3} .0308504
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2} .2427374{col 30}{space 2} .0535284{col 41}{space 1}    4.53{col 50}{space 3}0.000{col 58}{space 4} .1378238{col 71}{space 3} .3476511
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .0938632{col 30}{space 2} .0494037{col 41}{space 1}    1.90{col 50}{space 3}0.057{col 58}{space 4}-.0029662{col 71}{space 3} .1906927
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.889279{col 30}{space 2} .1436995{col 41}{space 1}   34.02{col 50}{space 3}0.000{col 58}{space 4} 4.607633{col 71}{space 3} 5.170925
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .70023067
         {txt}sigma_e {c |} {res} 1.2834502
             {txt}rho {c |} {res} .22938364{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est3
{txt}
{com}. 
. 
. xtreg hdd9  pdd9   $xlist  pdd9_mean $year_NIGER if country==1, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     6,536
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     3,837

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0397                                         {txt}min = {res}         1
{txt}     between = {res}0.2213                                         {txt}avg = {res}       1.7
{txt}     overall = {res}0.1727                                         {txt}max = {res}         2

                                                {txt}Wald chi2({res}21{txt})     =  {res}  1348.56
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,837} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .2418613{col 30}{space 2} .0352713{col 41}{space 1}    6.86{col 50}{space 3}0.000{col 58}{space 4} .1727308{col 71}{space 3} .3109918
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}  .013393{col 30}{space 2} .0065958{col 41}{space 1}    2.03{col 50}{space 3}0.042{col 58}{space 4} .0004655{col 71}{space 3} .0263206
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.1326112{col 30}{space 2} .1000549{col 41}{space 1}   -1.33{col 50}{space 3}0.185{col 58}{space 4}-.3287152{col 71}{space 3} .0634927
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0029101{col 30}{space 2} .0014282{col 41}{space 1}    2.04{col 50}{space 3}0.042{col 58}{space 4} .0001109{col 71}{space 3} .0057093
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}  .088006{col 30}{space 2} .0598281{col 41}{space 1}    1.47{col 50}{space 3}0.141{col 58}{space 4}-.0292549{col 71}{space 3} .2052669
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3483333{col 30}{space 2} .0456631{col 41}{space 1}    7.63{col 50}{space 3}0.000{col 58}{space 4} .2588353{col 71}{space 3} .4378313
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .3006591{col 30}{space 2} .1106177{col 41}{space 1}    2.72{col 50}{space 3}0.007{col 58}{space 4} .0838524{col 71}{space 3} .5174658
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0893745{col 30}{space 2} .0780906{col 41}{space 1}    1.14{col 50}{space 3}0.252{col 58}{space 4}-.0636804{col 71}{space 3} .2424293
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .3018629{col 30}{space 2} .1233802{col 41}{space 1}    2.45{col 50}{space 3}0.014{col 58}{space 4} .0600421{col 71}{space 3} .5436836
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1986832{col 30}{space 2} .0901497{col 41}{space 1}    2.20{col 50}{space 3}0.028{col 58}{space 4} .0219931{col 71}{space 3} .3753734
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}-.1745724{col 30}{space 2} .0683925{col 41}{space 1}   -2.55{col 50}{space 3}0.011{col 58}{space 4}-.3086192{col 71}{space 3}-.0405256
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1318193{col 30}{space 2} .0453711{col 41}{space 1}   -2.91{col 50}{space 3}0.004{col 58}{space 4}-.2207452{col 71}{space 3}-.0428935
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0014132{col 30}{space 2} .0015757{col 41}{space 1}   -0.90{col 50}{space 3}0.370{col 58}{space 4}-.0045015{col 71}{space 3} .0016752
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .2083843{col 30}{space 2} .2164151{col 41}{space 1}    0.96{col 50}{space 3}0.336{col 58}{space 4}-.2157814{col 71}{space 3} .6325501
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0526337{col 30}{space 2} .1330637{col 41}{space 1}    0.40{col 50}{space 3}0.692{col 58}{space 4}-.2081664{col 71}{space 3} .3134337
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .3337707{col 30}{space 2} .0954013{col 41}{space 1}    3.50{col 50}{space 3}0.000{col 58}{space 4} .1467876{col 71}{space 3} .5207538
{txt}electricity_mean {c |}{col 18}{res}{space 2}  .407959{col 30}{space 2} .1404658{col 41}{space 1}    2.90{col 50}{space 3}0.004{col 58}{space 4}  .132651{col 71}{space 3}  .683267
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .2162789{col 30}{space 2} .1109317{col 41}{space 1}    1.95{col 50}{space 3}0.051{col 58}{space 4}-.0011432{col 71}{space 3}  .433701
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .4538957{col 30}{space 2} .0840805{col 41}{space 1}    5.40{col 50}{space 3}0.000{col 58}{space 4} .2891009{col 71}{space 3} .6186906
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.2567401{col 30}{space 2} .0401505{col 41}{space 1}   -6.39{col 50}{space 3}0.000{col 58}{space 4}-.3354336{col 71}{space 3}-.1780466
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2} .2550797{col 30}{space 2}  .038422{col 41}{space 1}    6.64{col 50}{space 3}0.000{col 58}{space 4}  .179774{col 71}{space 3} .3303855
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.580461{col 30}{space 2} .1107819{col 41}{space 1}   41.35{col 50}{space 3}0.000{col 58}{space 4} 4.363332{col 71}{space 3} 4.797589
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .56375272
         {txt}sigma_e {c |} {res} 1.3958609
             {txt}rho {c |} {res} .14023955{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est4
{txt}
{com}. 
. 
. xtreg hdd9  pdd9   $xlist  pdd9_mean $year_NIGERIA if country==2, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    15,063
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     7,154

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0356                                         {txt}min = {res}         1
{txt}     between = {res}0.2969                                         {txt}avg = {res}       2.1
{txt}     overall = {res}0.2534                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}23{txt})     =  {res}  3871.97
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:7,154} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .0797371{col 30}{space 2} .0155474{col 41}{space 1}    5.13{col 50}{space 3}0.000{col 58}{space 4} .0492648{col 71}{space 3} .1102094
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0293148{col 30}{space 2} .0046704{col 41}{space 1}   -6.28{col 50}{space 3}0.000{col 58}{space 4}-.0384687{col 71}{space 3} -.020161
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .1558158{col 30}{space 2} .0540154{col 41}{space 1}    2.88{col 50}{space 3}0.004{col 58}{space 4} .0499477{col 71}{space 3}  .261684
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0046601{col 30}{space 2} .0009741{col 41}{space 1}    4.78{col 50}{space 3}0.000{col 58}{space 4} .0027509{col 71}{space 3} .0065693
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .3154281{col 30}{space 2} .0392348{col 41}{space 1}    8.04{col 50}{space 3}0.000{col 58}{space 4} .2385293{col 71}{space 3} .3923269
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .1907751{col 30}{space 2} .0286926{col 41}{space 1}    6.65{col 50}{space 3}0.000{col 58}{space 4} .1345385{col 71}{space 3} .2470116
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0158238{col 30}{space 2} .0419055{col 41}{space 1}    0.38{col 50}{space 3}0.706{col 58}{space 4}-.0663094{col 71}{space 3} .0979571
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1632202{col 30}{space 2} .0406531{col 41}{space 1}    4.01{col 50}{space 3}0.000{col 58}{space 4} .0835416{col 71}{space 3} .2428988
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0827451{col 30}{space 2} .0495446{col 41}{space 1}    1.67{col 50}{space 3}0.095{col 58}{space 4}-.0143606{col 71}{space 3} .1798508
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2569157{col 30}{space 2} .0571459{col 41}{space 1}    4.50{col 50}{space 3}0.000{col 58}{space 4} .1449117{col 71}{space 3} .3689197
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .3082281{col 30}{space 2} .0434577{col 41}{space 1}    7.09{col 50}{space 3}0.000{col 58}{space 4} .2230526{col 71}{space 3} .3934036
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} .0334789{col 30}{space 2} .0470724{col 41}{space 1}    0.71{col 50}{space 3}0.477{col 58}{space 4}-.0587814{col 71}{space 3} .1257392
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0087572{col 30}{space 2} .0068021{col 41}{space 1}   -1.29{col 50}{space 3}0.198{col 58}{space 4}-.0220891{col 71}{space 3} .0045746
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .3341661{col 30}{space 2} .0605789{col 41}{space 1}    5.52{col 50}{space 3}0.000{col 58}{space 4} .2154337{col 71}{space 3} .4528985
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0645349{col 30}{space 2} .0571875{col 41}{space 1}    1.13{col 50}{space 3}0.259{col 58}{space 4}-.0475506{col 71}{space 3} .1766204
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .7715254{col 30}{space 2}  .060225{col 41}{space 1}   12.81{col 50}{space 3}0.000{col 58}{space 4} .6534864{col 71}{space 3} .8895643
{txt}electricity_mean {c |}{col 18}{res}{space 2} .8428912{col 30}{space 2} .0617761{col 41}{space 1}   13.64{col 50}{space 3}0.000{col 58}{space 4} .7218123{col 71}{space 3} .9639701
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1399659{col 30}{space 2} .0743895{col 41}{space 1}    1.88{col 50}{space 3}0.060{col 58}{space 4}-.0058349{col 71}{space 3} .2857666
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.0525943{col 30}{space 2} .0556421{col 41}{space 1}   -0.95{col 50}{space 3}0.345{col 58}{space 4}-.1616508{col 71}{space 3} .0564623
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.0337268{col 30}{space 2} .0201497{col 41}{space 1}   -1.67{col 50}{space 3}0.094{col 58}{space 4}-.0732195{col 71}{space 3} .0057659
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.5672983{col 30}{space 2} .0333552{col 41}{space 1}  -17.01{col 50}{space 3}0.000{col 58}{space 4}-.6326732{col 71}{space 3}-.5019233
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2}-.5147852{col 30}{space 2} .0337128{col 41}{space 1}  -15.27{col 50}{space 3}0.000{col 58}{space 4}-.5808611{col 71}{space 3}-.4487092
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2} -.372811{col 30}{space 2} .0335485{col 41}{space 1}  -11.11{col 50}{space 3}0.000{col 58}{space 4}-.4385649{col 71}{space 3} -.307057
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.474605{col 30}{space 2} .0796199{col 41}{space 1}   56.20{col 50}{space 3}0.000{col 58}{space 4} 4.318553{col 71}{space 3} 4.630658
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .86808159
         {txt}sigma_e {c |} {res} 1.2228102
             {txt}rho {c |} {res} .33509226{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est5
{txt}
{com}. 
. 
. xtreg hdd9  pdd9   $xlist  pdd9_mean $year_TANZANIA if country==5, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    11,830
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     5,710

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0434                                         {txt}min = {res}         1
{txt}     between = {res}0.2265                                         {txt}avg = {res}       2.1
{txt}     overall = {res}0.1812                                         {txt}max = {res}         5

                                                {txt}Wald chi2({res}23{txt})     =  {res}  2101.06
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:5,710} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .1931047{col 30}{space 2} .0136841{col 41}{space 1}   14.11{col 50}{space 3}0.000{col 58}{space 4} .1662844{col 71}{space 3}  .219925
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0093469{col 30}{space 2} .0054007{col 41}{space 1}   -1.73{col 50}{space 3}0.084{col 58}{space 4}-.0199322{col 71}{space 3} .0012383
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0479867{col 30}{space 2} .0651529{col 41}{space 1}    0.74{col 50}{space 3}0.461{col 58}{space 4}-.0797106{col 71}{space 3} .1756841
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0022084{col 30}{space 2} .0010512{col 41}{space 1}   -2.10{col 50}{space 3}0.036{col 58}{space 4}-.0042687{col 71}{space 3}-.0001482
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0494775{col 30}{space 2} .0370294{col 41}{space 1}    1.34{col 50}{space 3}0.181{col 58}{space 4}-.0230988{col 71}{space 3} .1220538
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2753447{col 30}{space 2} .0351178{col 41}{space 1}    7.84{col 50}{space 3}0.000{col 58}{space 4} .2065151{col 71}{space 3} .3441742
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2532299{col 30}{space 2} .0848296{col 41}{space 1}    2.99{col 50}{space 3}0.003{col 58}{space 4} .0869668{col 71}{space 3}  .419493
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2435248{col 30}{space 2} .0478541{col 41}{space 1}    5.09{col 50}{space 3}0.000{col 58}{space 4} .1497325{col 71}{space 3} .3373172
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0512096{col 30}{space 2} .0549581{col 41}{space 1}    0.93{col 50}{space 3}0.351{col 58}{space 4}-.0565064{col 71}{space 3} .1589255
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1071934{col 30}{space 2} .0383951{col 41}{space 1}    2.79{col 50}{space 3}0.005{col 58}{space 4} .0319404{col 71}{space 3} .1824463
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2110457{col 30}{space 2}  .040364{col 41}{space 1}    5.23{col 50}{space 3}0.000{col 58}{space 4} .1319337{col 71}{space 3} .2901576
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1731841{col 30}{space 2} .0337737{col 41}{space 1}   -5.13{col 50}{space 3}0.000{col 58}{space 4}-.2393793{col 71}{space 3}-.1069888
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0019761{col 30}{space 2} .0032637{col 41}{space 1}   -0.61{col 50}{space 3}0.545{col 58}{space 4}-.0083727{col 71}{space 3} .0044206
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0203958{col 30}{space 2} .0329862{col 41}{space 1}    0.62{col 50}{space 3}0.536{col 58}{space 4}-.0442561{col 71}{space 3} .0850476
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .2808998{col 30}{space 2} .1125677{col 41}{space 1}    2.50{col 50}{space 3}0.013{col 58}{space 4} .0602712{col 71}{space 3} .5015285
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .4428084{col 30}{space 2} .0656437{col 41}{space 1}    6.75{col 50}{space 3}0.000{col 58}{space 4} .3141491{col 71}{space 3} .5714678
{txt}electricity_mean {c |}{col 18}{res}{space 2}  .601696{col 30}{space 2} .0739958{col 41}{space 1}    8.13{col 50}{space 3}0.000{col 58}{space 4} .4566668{col 71}{space 3} .7467252
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .0452153{col 30}{space 2}   .05518{col 41}{space 1}    0.82{col 50}{space 3}0.413{col 58}{space 4}-.0629356{col 71}{space 3} .1533661
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .3015236{col 30}{space 2} .0571035{col 41}{space 1}    5.28{col 50}{space 3}0.000{col 58}{space 4} .1896027{col 71}{space 3} .4134445
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.1198071{col 30}{space 2} .0170128{col 41}{space 1}   -7.04{col 50}{space 3}0.000{col 58}{space 4}-.1531515{col 71}{space 3}-.0864627
{txt}{space 10}year_1 {c |}{col 18}{res}{space 2}-.0253327{col 30}{space 2}  .037459{col 41}{space 1}   -0.68{col 50}{space 3}0.499{col 58}{space 4}-.0987509{col 71}{space 3} .0480855
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2} .0470319{col 30}{space 2} .0322499{col 41}{space 1}    1.46{col 50}{space 3}0.145{col 58}{space 4}-.0161767{col 71}{space 3} .1102406
{txt}{space 10}year_7 {c |}{col 18}{res}{space 2} .0483065{col 30}{space 2} .0352444{col 41}{space 1}    1.37{col 50}{space 3}0.170{col 58}{space 4}-.0207712{col 71}{space 3} .1173842
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.485695{col 30}{space 2} .0833595{col 41}{space 1}   53.81{col 50}{space 3}0.000{col 58}{space 4} 4.322314{col 71}{space 3} 4.649077
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .78023597
         {txt}sigma_e {c |} {res} 1.2092564
             {txt}rho {c |} {res} .29393906{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est6
{txt}
{com}. 
. 
. xtreg hdd9  pdd9   $xlist  pdd9_mean  $year_UGANDA if country==4, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    16,114
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     4,402

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0485                                         {txt}min = {res}         1
{txt}     between = {res}0.2727                                         {txt}avg = {res}       3.7
{txt}     overall = {res}0.1902                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}25{txt})     =  {res}  2532.02
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:4,402} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .0994732{col 30}{space 2} .0113779{col 41}{space 1}    8.74{col 50}{space 3}0.000{col 58}{space 4} .0771729{col 71}{space 3} .1217735
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0118347{col 30}{space 2} .0055723{col 41}{space 1}    2.12{col 50}{space 3}0.034{col 58}{space 4} .0009131{col 71}{space 3} .0227563
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0639706{col 30}{space 2} .0594067{col 41}{space 1}    1.08{col 50}{space 3}0.282{col 58}{space 4}-.0524644{col 71}{space 3} .1804056
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0012154{col 30}{space 2} .0010263{col 41}{space 1}   -1.18{col 50}{space 3}0.236{col 58}{space 4} -.003227{col 71}{space 3} .0007962
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}  .058616{col 30}{space 2} .0344209{col 41}{space 1}    1.70{col 50}{space 3}0.089{col 58}{space 4}-.0088478{col 71}{space 3} .1260798
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3265784{col 30}{space 2} .0337857{col 41}{space 1}    9.67{col 50}{space 3}0.000{col 58}{space 4} .2603596{col 71}{space 3} .3927972
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2298902{col 30}{space 2}   .05619{col 41}{space 1}    4.09{col 50}{space 3}0.000{col 58}{space 4} .1197599{col 71}{space 3} .3400205
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2447202{col 30}{space 2} .0373205{col 41}{space 1}    6.56{col 50}{space 3}0.000{col 58}{space 4} .1715733{col 71}{space 3} .3178671
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .3422081{col 30}{space 2} .0378166{col 41}{space 1}    9.05{col 50}{space 3}0.000{col 58}{space 4} .2680889{col 71}{space 3} .4163273
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0415031{col 30}{space 2} .0304786{col 41}{space 1}    1.36{col 50}{space 3}0.173{col 58}{space 4}-.0182339{col 71}{space 3} .1012401
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .1958873{col 30}{space 2} .0320586{col 41}{space 1}    6.11{col 50}{space 3}0.000{col 58}{space 4} .1330536{col 71}{space 3}  .258721
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0152503{col 30}{space 2} .0250389{col 41}{space 1}   -0.61{col 50}{space 3}0.542{col 58}{space 4}-.0643256{col 71}{space 3}  .033825
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0002386{col 30}{space 2} .0016131{col 41}{space 1}    0.15{col 50}{space 3}0.882{col 58}{space 4}-.0029231{col 71}{space 3} .0034002
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0167297{col 30}{space 2} .0279384{col 41}{space 1}    0.60{col 50}{space 3}0.549{col 58}{space 4}-.0380284{col 71}{space 3} .0714879
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1441942{col 30}{space 2} .0874612{col 41}{space 1}    1.65{col 50}{space 3}0.099{col 58}{space 4}-.0272267{col 71}{space 3} .3156151
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .3742288{col 30}{space 2} .0625765{col 41}{space 1}    5.98{col 50}{space 3}0.000{col 58}{space 4} .2515812{col 71}{space 3} .4968764
{txt}electricity_mean {c |}{col 18}{res}{space 2} .4300925{col 30}{space 2} .0697059{col 41}{space 1}    6.17{col 50}{space 3}0.000{col 58}{space 4} .2934714{col 71}{space 3} .5667136
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}  .178564{col 30}{space 2} .0559109{col 41}{space 1}    3.19{col 50}{space 3}0.001{col 58}{space 4} .0689806{col 71}{space 3} .2881474
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .3427401{col 30}{space 2} .0543074{col 41}{space 1}    6.31{col 50}{space 3}0.000{col 58}{space 4} .2362995{col 71}{space 3} .4491808
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .0239568{col 30}{space 2} .0173747{col 41}{space 1}    1.38{col 50}{space 3}0.168{col 58}{space 4} -.010097{col 71}{space 3} .0580106
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.1296924{col 30}{space 2} .0382397{col 41}{space 1}   -3.39{col 50}{space 3}0.001{col 58}{space 4}-.2046409{col 71}{space 3} -.054744
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2}-.0485443{col 30}{space 2} .0333045{col 41}{space 1}   -1.46{col 50}{space 3}0.145{col 58}{space 4}  -.11382{col 71}{space 3} .0167313
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .3397759{col 30}{space 2} .0338467{col 41}{space 1}   10.04{col 50}{space 3}0.000{col 58}{space 4} .2734376{col 71}{space 3} .4061143
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2} .0846579{col 30}{space 2} .0339696{col 41}{space 1}    2.49{col 50}{space 3}0.013{col 58}{space 4} .0180786{col 71}{space 3} .1512372
{txt}{space 9}year_10 {c |}{col 18}{res}{space 2} .2929945{col 30}{space 2} .0321095{col 41}{space 1}    9.12{col 50}{space 3}0.000{col 58}{space 4} .2300611{col 71}{space 3}  .355928
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 3.866225{col 30}{space 2} .0883898{col 41}{space 1}   43.74{col 50}{space 3}0.000{col 58}{space 4} 3.692984{col 71}{space 3} 4.039466
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .81142007
         {txt}sigma_e {c |} {res} 1.2635858
             {txt}rho {c |} {res} .29196783{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est7
{txt}
{com}. esttab using  S6.rtf, se replace star(* 0.1 ** 0.05 *** 0.01) cells (b(star fmt(%9.3f)) se (par(( )) fmt(%9.3f)))  stats(N r2_b  r2_w r2_o p, fmt(%4.0f %4.3f %4.3f %6.3f)) keep(pdd9   $xlist  pdd9_mean _cons )
{res}{txt}(note: file S6.rtf not found)
(output written to {browse  `"S6.rtf"'})

{com}. 
. 
. ********************************************************************************
. *                                Table S7                                      *
. ********************************************************************************
. eststo clear
{txt}
{com}. xtreg hdd9  pdd9_vill sum_vill  $xlist  pdd9_mean_vill i.country i.year   , cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    65,579
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}    27,229

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0219                                         {txt}min = {res}         1
{txt}     between = {res}0.3733                                         {txt}avg = {res}       2.4
{txt}     overall = {res}0.2881                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}36{txt})     =  {res} 20864.73
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:27,229} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_vill {c |}{col 18}{res}{space 2} .0437778{col 30}{space 2} .0071365{col 41}{space 1}    6.13{col 50}{space 3}0.000{col 58}{space 4} .0297906{col 71}{space 3}  .057765
{txt}{space 8}sum_vill {c |}{col 18}{res}{space 2}-.0494106{col 30}{space 2} .0024984{col 41}{space 1}  -19.78{col 50}{space 3}0.000{col 58}{space 4}-.0543075{col 71}{space 3}-.0445138
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0037478{col 30}{space 2} .0024298{col 41}{space 1}    1.54{col 50}{space 3}0.123{col 58}{space 4}-.0010145{col 71}{space 3} .0085101
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0463807{col 30}{space 2} .0276535{col 41}{space 1}    1.68{col 50}{space 3}0.094{col 58}{space 4}-.0078191{col 71}{space 3} .1005805
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0000317{col 30}{space 2} .0004617{col 41}{space 1}    0.07{col 50}{space 3}0.945{col 58}{space 4}-.0008732{col 71}{space 3} .0009366
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0347232{col 30}{space 2} .0168878{col 41}{space 1}    2.06{col 50}{space 3}0.040{col 58}{space 4} .0016238{col 71}{space 3} .0678227
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2981026{col 30}{space 2} .0147565{col 41}{space 1}   20.20{col 50}{space 3}0.000{col 58}{space 4} .2691804{col 71}{space 3} .3270247
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1241965{col 30}{space 2} .0294339{col 41}{space 1}    4.22{col 50}{space 3}0.000{col 58}{space 4} .0665072{col 71}{space 3} .1818858
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1724967{col 30}{space 2} .0193431{col 41}{space 1}    8.92{col 50}{space 3}0.000{col 58}{space 4}  .134585{col 71}{space 3} .2104085
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1425662{col 30}{space 2} .0228219{col 41}{space 1}    6.25{col 50}{space 3}0.000{col 58}{space 4}  .097836{col 71}{space 3} .1872964
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1273375{col 30}{space 2} .0199251{col 41}{space 1}    6.39{col 50}{space 3}0.000{col 58}{space 4} .0882849{col 71}{space 3}   .16639
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2146016{col 30}{space 2} .0183202{col 41}{space 1}   11.71{col 50}{space 3}0.000{col 58}{space 4} .1786947{col 71}{space 3} .2505085
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0347813{col 30}{space 2} .0142726{col 41}{space 1}   -2.44{col 50}{space 3}0.015{col 58}{space 4}-.0627551{col 71}{space 3}-.0068074
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0006481{col 30}{space 2} .0010929{col 41}{space 1}    0.59{col 50}{space 3}0.553{col 58}{space 4}-.0014939{col 71}{space 3} .0027901
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1643842{col 30}{space 2} .0159668{col 41}{space 1}   10.30{col 50}{space 3}0.000{col 58}{space 4} .1330899{col 71}{space 3} .1956786
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0440769{col 30}{space 2} .0394896{col 41}{space 1}    1.12{col 50}{space 3}0.264{col 58}{space 4}-.0333214{col 71}{space 3} .1214752
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .5268787{col 30}{space 2} .0280367{col 41}{space 1}   18.79{col 50}{space 3}0.000{col 58}{space 4} .4719278{col 71}{space 3} .5818295
{txt}electricity_mean {c |}{col 18}{res}{space 2} .6096075{col 30}{space 2} .0309691{col 41}{space 1}   19.68{col 50}{space 3}0.000{col 58}{space 4} .5489091{col 71}{space 3} .6703059
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1222808{col 30}{space 2} .0294909{col 41}{space 1}    4.15{col 50}{space 3}0.000{col 58}{space 4} .0644797{col 71}{space 3}  .180082
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .1239314{col 30}{space 2} .0255049{col 41}{space 1}    4.86{col 50}{space 3}0.000{col 58}{space 4} .0739427{col 71}{space 3} .1739201
{txt}{space 2}pdd9_mean_vill {c |}{col 18}{res}{space 2} .0843952{col 30}{space 2} .0090772{col 41}{space 1}    9.30{col 50}{space 3}0.000{col 58}{space 4} .0666042{col 71}{space 3} .1021862
{txt}{space 16} {c |}
{space 9}country {c |}
{space 8}Nigeria  {c |}{col 18}{res}{space 2}-.5864976{col 30}{space 2} .0332015{col 41}{space 1}  -17.66{col 50}{space 3}0.000{col 58}{space 4}-.6515714{col 71}{space 3}-.5214239
{txt}{space 7}Ethiopia  {c |}{col 18}{res}{space 2}-1.798805{col 30}{space 2} .0340658{col 41}{space 1}  -52.80{col 50}{space 3}0.000{col 58}{space 4}-1.865573{col 71}{space 3}-1.732037
{txt}{space 9}Uganda  {c |}{col 18}{res}{space 2}-.7861785{col 30}{space 2} .0345986{col 41}{space 1}  -22.72{col 50}{space 3}0.000{col 58}{space 4}-.8539905{col 71}{space 3}-.7183664
{txt}{space 7}Tanzania  {c |}{col 18}{res}{space 2}-.6806499{col 30}{space 2}  .037041{col 41}{space 1}  -18.38{col 50}{space 3}0.000{col 58}{space 4} -.753249{col 71}{space 3}-.6080508
{txt}{space 9}Malawi  {c |}{col 18}{res}{space 2} .2354971{col 30}{space 2} .0420555{col 41}{space 1}    5.60{col 50}{space 3}0.000{col 58}{space 4} .1530699{col 71}{space 3} .3179244
{txt}{space 16} {c |}
{space 12}year {c |}
{space 11}2009  {c |}{col 18}{res}{space 2}-.2273892{col 30}{space 2} .0463509{col 41}{space 1}   -4.91{col 50}{space 3}0.000{col 58}{space 4}-.3182353{col 71}{space 3} -.136543
{txt}{space 11}2010  {c |}{col 18}{res}{space 2} .0683135{col 30}{space 2} .0353012{col 41}{space 1}    1.94{col 50}{space 3}0.053{col 58}{space 4}-.0008756{col 71}{space 3} .1375026
{txt}{space 11}2011  {c |}{col 18}{res}{space 2} .0897435{col 30}{space 2} .0389891{col 41}{space 1}    2.30{col 50}{space 3}0.021{col 58}{space 4} .0133264{col 71}{space 3} .1661606
{txt}{space 11}2012  {c |}{col 18}{res}{space 2} .0606066{col 30}{space 2} .0358046{col 41}{space 1}    1.69{col 50}{space 3}0.091{col 58}{space 4}-.0095691{col 71}{space 3} .1307823
{txt}{space 11}2013  {c |}{col 18}{res}{space 2} .1544148{col 30}{space 2} .0394444{col 41}{space 1}    3.91{col 50}{space 3}0.000{col 58}{space 4} .0771051{col 71}{space 3} .2317245
{txt}{space 11}2014  {c |}{col 18}{res}{space 2}-.0372272{col 30}{space 2} .0397642{col 41}{space 1}   -0.94{col 50}{space 3}0.349{col 58}{space 4}-.1151636{col 71}{space 3} .0407091
{txt}{space 11}2015  {c |}{col 18}{res}{space 2} .2217062{col 30}{space 2} .0382131{col 41}{space 1}    5.80{col 50}{space 3}0.000{col 58}{space 4} .1468099{col 71}{space 3} .2966025
{txt}{space 11}2016  {c |}{col 18}{res}{space 2}-.2184384{col 30}{space 2} .0587745{col 41}{space 1}   -3.72{col 50}{space 3}0.000{col 58}{space 4}-.3336343{col 71}{space 3}-.1032425
{txt}{space 11}2018  {c |}{col 18}{res}{space 2} .4901667{col 30}{space 2}  .040204{col 41}{space 1}   12.19{col 50}{space 3}0.000{col 58}{space 4} .4113682{col 71}{space 3} .5689651
{txt}{space 11}2019  {c |}{col 18}{res}{space 2} .0207715{col 30}{space 2} .0392038{col 41}{space 1}    0.53{col 50}{space 3}0.596{col 58}{space 4}-.0560665{col 71}{space 3} .0976095
{txt}{space 16} {c |}
{space 11}_cons {c |}{col 18}{res}{space 2} 4.696564{col 30}{space 2} .0607587{col 41}{space 1}   77.30{col 50}{space 3}0.000{col 58}{space 4}  4.57748{col 71}{space 3} 4.815649
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .78888658
         {txt}sigma_e {c |} {res} 1.2371012
             {txt}rho {c |} {res} .28909012{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est1
{txt}
{com}. 
. xtreg hdd9  pdd9_vill sum_vill  $xlist  pdd9_mean_vill $year_ETHIOPIA if country==3, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    11,410
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     4,555

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0188                                         {txt}min = {res}         1
{txt}     between = {res}0.3385                                         {txt}avg = {res}       2.5
{txt}     overall = {res}0.2264                                         {txt}max = {res}         3

                                                {txt}Wald chi2({res}22{txt})     =  {res}  2542.72
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:4,555} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_vill {c |}{col 18}{res}{space 2} .0520459{col 30}{space 2} .0150217{col 41}{space 1}    3.46{col 50}{space 3}0.001{col 58}{space 4} .0226039{col 71}{space 3} .0814878
{txt}{space 8}sum_vill {c |}{col 18}{res}{space 2}-.0486224{col 30}{space 2} .0079267{col 41}{space 1}   -6.13{col 50}{space 3}0.000{col 58}{space 4}-.0641584{col 71}{space 3}-.0330863
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0522133{col 30}{space 2} .0069888{col 41}{space 1}    7.47{col 50}{space 3}0.000{col 58}{space 4} .0385155{col 71}{space 3}  .065911
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0536411{col 30}{space 2} .0571637{col 41}{space 1}   -0.94{col 50}{space 3}0.348{col 58}{space 4}-.1656799{col 71}{space 3} .0583978
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0033175{col 30}{space 2} .0009874{col 41}{space 1}   -3.36{col 50}{space 3}0.001{col 58}{space 4}-.0052527{col 71}{space 3}-.0013823
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0521864{col 30}{space 2} .0357111{col 41}{space 1}   -1.46{col 50}{space 3}0.144{col 58}{space 4}-.1221787{col 71}{space 3}  .017806
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3750429{col 30}{space 2} .0312713{col 41}{space 1}   11.99{col 50}{space 3}0.000{col 58}{space 4} .3137523{col 71}{space 3} .4363335
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}-.2125058{col 30}{space 2} .1565102{col 41}{space 1}   -1.36{col 50}{space 3}0.175{col 58}{space 4}-.5192602{col 71}{space 3} .0942486
{txt}{space 11}phone {c |}{col 18}{res}{space 2}  .184056{col 30}{space 2} .0378492{col 41}{space 1}    4.86{col 50}{space 3}0.000{col 58}{space 4}  .109873{col 71}{space 3}  .258239
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1634309{col 30}{space 2}  .046265{col 41}{space 1}    3.53{col 50}{space 3}0.000{col 58}{space 4} .0727532{col 71}{space 3} .2541086
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0764253{col 30}{space 2} .0630848{col 41}{space 1}    1.21{col 50}{space 3}0.226{col 58}{space 4}-.0472185{col 71}{space 3} .2000692
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2241372{col 30}{space 2} .0499909{col 41}{space 1}    4.48{col 50}{space 3}0.000{col 58}{space 4} .1261568{col 71}{space 3} .3221175
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1103295{col 30}{space 2} .0295293{col 41}{space 1}   -3.74{col 50}{space 3}0.000{col 58}{space 4}-.1682059{col 71}{space 3}-.0524532
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0140295{col 30}{space 2} .0036486{col 41}{space 1}    3.85{col 50}{space 3}0.000{col 58}{space 4} .0068784{col 71}{space 3} .0211807
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .2533167{col 30}{space 2} .0308971{col 41}{space 1}    8.20{col 50}{space 3}0.000{col 58}{space 4} .1927595{col 71}{space 3} .3138739
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} 1.024552{col 30}{space 2} .2624628{col 41}{space 1}    3.90{col 50}{space 3}0.000{col 58}{space 4} .5101349{col 71}{space 3}  1.53897
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .4756492{col 30}{space 2} .0569103{col 41}{space 1}    8.36{col 50}{space 3}0.000{col 58}{space 4} .3641071{col 71}{space 3} .5871912
{txt}electricity_mean {c |}{col 18}{res}{space 2} .3728838{col 30}{space 2} .0691018{col 41}{space 1}    5.40{col 50}{space 3}0.000{col 58}{space 4} .2374467{col 71}{space 3} .5083209
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .4263647{col 30}{space 2} .0970235{col 41}{space 1}    4.39{col 50}{space 3}0.000{col 58}{space 4} .2362022{col 71}{space 3} .6165272
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .0567792{col 30}{space 2} .0634387{col 41}{space 1}    0.90{col 50}{space 3}0.371{col 58}{space 4}-.0675584{col 71}{space 3} .1811168
{txt}{space 2}pdd9_mean_vill {c |}{col 18}{res}{space 2} .0790103{col 30}{space 2} .0181094{col 41}{space 1}    4.36{col 50}{space 3}0.000{col 58}{space 4} .0435166{col 71}{space 3}  .114504
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}-.1369882{col 30}{space 2} .0222928{col 41}{space 1}   -6.14{col 50}{space 3}0.000{col 58}{space 4}-.1806813{col 71}{space 3}-.0932952
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 3.066452{col 30}{space 2} .1031008{col 41}{space 1}   29.74{col 50}{space 3}0.000{col 58}{space 4} 2.864378{col 71}{space 3} 3.268526
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .72872341
         {txt}sigma_e {c |} {res} 1.0778015
             {txt}rho {c |} {res} .31372346{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est2
{txt}
{com}. 
. xtreg hdd9  pdd9_vill sum_vill  $xlist  pdd9_mean_vill $year_MALAWI  if country==6, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     4,626
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     1,571

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0210                                         {txt}min = {res}         1
{txt}     between = {res}0.3941                                         {txt}avg = {res}       2.9
{txt}     overall = {res}0.2774                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}23{txt})     =  {res}  1544.49
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:1,571} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_vill {c |}{col 18}{res}{space 2} .0655642{col 30}{space 2} .0255957{col 41}{space 1}    2.56{col 50}{space 3}0.010{col 58}{space 4} .0153975{col 71}{space 3} .1157309
{txt}{space 8}sum_vill {c |}{col 18}{res}{space 2}-.0380229{col 30}{space 2} .0100863{col 41}{space 1}   -3.77{col 50}{space 3}0.000{col 58}{space 4}-.0577917{col 71}{space 3}-.0182541
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0000461{col 30}{space 2}  .011206{col 41}{space 1}   -0.00{col 50}{space 3}0.997{col 58}{space 4}-.0220095{col 71}{space 3} .0219174
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.2440043{col 30}{space 2} .1029867{col 41}{space 1}   -2.37{col 50}{space 3}0.018{col 58}{space 4}-.4458546{col 71}{space 3}-.0421541
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0019926{col 30}{space 2} .0017105{col 41}{space 1}   -1.16{col 50}{space 3}0.244{col 58}{space 4}-.0053451{col 71}{space 3}   .00136
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.1026714{col 30}{space 2} .0599256{col 41}{space 1}   -1.71{col 50}{space 3}0.087{col 58}{space 4}-.2201233{col 71}{space 3} .0147806
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3069651{col 30}{space 2} .0584492{col 41}{space 1}    5.25{col 50}{space 3}0.000{col 58}{space 4} .1924067{col 71}{space 3} .4215235
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2474592{col 30}{space 2} .1917102{col 41}{space 1}    1.29{col 50}{space 3}0.197{col 58}{space 4}-.1282859{col 71}{space 3} .6232043
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1008257{col 30}{space 2} .0695221{col 41}{space 1}    1.45{col 50}{space 3}0.147{col 58}{space 4} -.035435{col 71}{space 3} .2370865
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}  .189066{col 30}{space 2} .1408435{col 41}{space 1}    1.34{col 50}{space 3}0.179{col 58}{space 4}-.0869822{col 71}{space 3} .4651142
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1321611{col 30}{space 2} .0813677{col 41}{space 1}    1.62{col 50}{space 3}0.104{col 58}{space 4}-.0273166{col 71}{space 3} .2916389
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2510517{col 30}{space 2} .0561192{col 41}{space 1}    4.47{col 50}{space 3}0.000{col 58}{space 4}   .14106{col 71}{space 3} .3610433
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1340599{col 30}{space 2} .0438972{col 41}{space 1}   -3.05{col 50}{space 3}0.002{col 58}{space 4}-.2200968{col 71}{space 3} -.048023
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .1126935{col 30}{space 2} .0359349{col 41}{space 1}    3.14{col 50}{space 3}0.002{col 58}{space 4} .0422624{col 71}{space 3} .1831246
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0962443{col 30}{space 2}  .062407{col 41}{space 1}    1.54{col 50}{space 3}0.123{col 58}{space 4}-.0260712{col 71}{space 3} .2185598
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1439232{col 30}{space 2} .3352119{col 41}{space 1}    0.43{col 50}{space 3}0.668{col 58}{space 4}  -.51308{col 71}{space 3} .8009265
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .6998549{col 30}{space 2} .1091614{col 41}{space 1}    6.41{col 50}{space 3}0.000{col 58}{space 4} .4859026{col 71}{space 3} .9138073
{txt}electricity_mean {c |}{col 18}{res}{space 2} .8034316{col 30}{space 2} .1780722{col 41}{space 1}    4.51{col 50}{space 3}0.000{col 58}{space 4} .4544165{col 71}{space 3} 1.152447
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .2635061{col 30}{space 2} .1165759{col 41}{space 1}    2.26{col 50}{space 3}0.024{col 58}{space 4} .0350215{col 71}{space 3} .4919908
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}  .235637{col 30}{space 2} .1000076{col 41}{space 1}    2.36{col 50}{space 3}0.018{col 58}{space 4} .0396258{col 71}{space 3} .4316483
{txt}{space 2}pdd9_mean_vill {c |}{col 18}{res}{space 2}-.0457961{col 30}{space 2}   .03994{col 41}{space 1}   -1.15{col 50}{space 3}0.252{col 58}{space 4} -.124077{col 71}{space 3} .0324848
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2} .3235779{col 30}{space 2} .0612609{col 41}{space 1}    5.28{col 50}{space 3}0.000{col 58}{space 4} .2035087{col 71}{space 3} .4436471
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .1149873{col 30}{space 2} .0501013{col 41}{space 1}    2.30{col 50}{space 3}0.022{col 58}{space 4} .0167906{col 71}{space 3} .2131839
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 5.391343{col 30}{space 2} .2146344{col 41}{space 1}   25.12{col 50}{space 3}0.000{col 58}{space 4} 4.970667{col 71}{space 3} 5.812019
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .69630733
         {txt}sigma_e {c |} {res} 1.2890757
             {txt}rho {c |} {res} .22587017{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est3
{txt}
{com}. 
. xtreg hdd9  pdd9_vill sum_vill  $xlist  pdd9_mean_vill $year_NIGER if country==1, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     6,536
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     3,837

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0237                                         {txt}min = {res}         1
{txt}     between = {res}0.2450                                         {txt}avg = {res}       1.7
{txt}     overall = {res}0.1839                                         {txt}max = {res}         2

                                                {txt}Wald chi2({res}22{txt})     =  {res}  1450.23
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,837} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_vill {c |}{col 18}{res}{space 2} .1124152{col 30}{space 2} .0308949{col 41}{space 1}    3.64{col 50}{space 3}0.000{col 58}{space 4} .0518623{col 71}{space 3} .1729681
{txt}{space 8}sum_vill {c |}{col 18}{res}{space 2}-.0626683{col 30}{space 2} .0063129{col 41}{space 1}   -9.93{col 50}{space 3}0.000{col 58}{space 4}-.0750413{col 71}{space 3}-.0502954
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0192368{col 30}{space 2} .0063327{col 41}{space 1}    3.04{col 50}{space 3}0.002{col 58}{space 4}  .006825{col 71}{space 3} .0316486
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0956448{col 30}{space 2} .0997031{col 41}{space 1}   -0.96{col 50}{space 3}0.337{col 58}{space 4}-.2910592{col 71}{space 3} .0997696
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0013645{col 30}{space 2} .0014196{col 41}{space 1}    0.96{col 50}{space 3}0.336{col 58}{space 4}-.0014179{col 71}{space 3}  .004147
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0453697{col 30}{space 2} .0587459{col 41}{space 1}    0.77{col 50}{space 3}0.440{col 58}{space 4}-.0697702{col 71}{space 3} .1605095
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3347186{col 30}{space 2} .0453829{col 41}{space 1}    7.38{col 50}{space 3}0.000{col 58}{space 4} .2457697{col 71}{space 3} .4236675
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}  .325666{col 30}{space 2} .1119055{col 41}{space 1}    2.91{col 50}{space 3}0.004{col 58}{space 4} .1063351{col 71}{space 3} .5449968
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1031145{col 30}{space 2} .0790499{col 41}{space 1}    1.30{col 50}{space 3}0.192{col 58}{space 4}-.0518204{col 71}{space 3} .2580495
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .2284768{col 30}{space 2} .1255288{col 41}{space 1}    1.82{col 50}{space 3}0.069{col 58}{space 4}-.0175552{col 71}{space 3} .4745088
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2107766{col 30}{space 2} .0909195{col 41}{space 1}    2.32{col 50}{space 3}0.020{col 58}{space 4} .0325777{col 71}{space 3} .3889755
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}-.1613506{col 30}{space 2} .0696526{col 41}{space 1}   -2.32{col 50}{space 3}0.021{col 58}{space 4}-.2978672{col 71}{space 3} -.024834
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0678166{col 30}{space 2} .0453556{col 41}{space 1}   -1.50{col 50}{space 3}0.135{col 58}{space 4} -.156712{col 71}{space 3} .0210788
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0007767{col 30}{space 2}  .001508{col 41}{space 1}   -0.52{col 50}{space 3}0.606{col 58}{space 4}-.0037323{col 71}{space 3} .0021788
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .3001149{col 30}{space 2} .2190299{col 41}{space 1}    1.37{col 50}{space 3}0.171{col 58}{space 4}-.1291757{col 71}{space 3} .7294056
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}-.0007937{col 30}{space 2}  .133915{col 41}{space 1}   -0.01{col 50}{space 3}0.995{col 58}{space 4}-.2632623{col 71}{space 3} .2616749
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .1409804{col 30}{space 2} .0971091{col 41}{space 1}    1.45{col 50}{space 3}0.147{col 58}{space 4}-.0493499{col 71}{space 3} .3313107
{txt}electricity_mean {c |}{col 18}{res}{space 2} .2012897{col 30}{space 2} .1448711{col 41}{space 1}    1.39{col 50}{space 3}0.165{col 58}{space 4}-.0826524{col 71}{space 3} .4852319
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .0581451{col 30}{space 2} .1112941{col 41}{space 1}    0.52{col 50}{space 3}0.601{col 58}{space 4}-.1599874{col 71}{space 3} .2762776
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .3640445{col 30}{space 2} .0853135{col 41}{space 1}    4.27{col 50}{space 3}0.000{col 58}{space 4} .1968332{col 71}{space 3} .5312558
{txt}{space 2}pdd9_mean_vill {c |}{col 18}{res}{space 2}-.0477788{col 30}{space 2} .0354841{col 41}{space 1}   -1.35{col 50}{space 3}0.178{col 58}{space 4}-.1173262{col 71}{space 3} .0217687
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2} .2807444{col 30}{space 2} .0392336{col 41}{space 1}    7.16{col 50}{space 3}0.000{col 58}{space 4} .2038479{col 71}{space 3} .3576408
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 5.304629{col 30}{space 2} .1361428{col 41}{space 1}   38.96{col 50}{space 3}0.000{col 58}{space 4} 5.037793{col 71}{space 3} 5.571464
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .50240752
         {txt}sigma_e {c |} {res} 1.4060479
             {txt}rho {c |} {res}  .1132211{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est4
{txt}
{com}. 
. 
. xtreg hdd9  pdd9_vill sum_vill  $xlist  pdd9_mean_vill $year_NIGERIA if country==2, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    15,063
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     7,154

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0348                                         {txt}min = {res}         1
{txt}     between = {res}0.3218                                         {txt}avg = {res}       2.1
{txt}     overall = {res}0.2718                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}24{txt})     =  {res}  4396.16
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:7,154} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_vill {c |}{col 18}{res}{space 2} .0665621{col 30}{space 2} .0156285{col 41}{space 1}    4.26{col 50}{space 3}0.000{col 58}{space 4} .0359308{col 71}{space 3} .0971935
{txt}{space 8}sum_vill {c |}{col 18}{res}{space 2}-.0918446{col 30}{space 2} .0071897{col 41}{space 1}  -12.77{col 50}{space 3}0.000{col 58}{space 4}-.1059361{col 71}{space 3}-.0777531
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0145126{col 30}{space 2} .0046655{col 41}{space 1}   -3.11{col 50}{space 3}0.002{col 58}{space 4}-.0236567{col 71}{space 3}-.0053684
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}  .148199{col 30}{space 2} .0536325{col 41}{space 1}    2.76{col 50}{space 3}0.006{col 58}{space 4} .0430811{col 71}{space 3} .2533168
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0031477{col 30}{space 2} .0009595{col 41}{space 1}    3.28{col 50}{space 3}0.001{col 58}{space 4} .0012671{col 71}{space 3} .0050282
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .2558029{col 30}{space 2} .0389368{col 41}{space 1}    6.57{col 50}{space 3}0.000{col 58}{space 4} .1794881{col 71}{space 3} .3321176
{txt}{space 7}head_read {c |}{col 18}{res}{space 2}  .174215{col 30}{space 2} .0283255{col 41}{space 1}    6.15{col 50}{space 3}0.000{col 58}{space 4}  .118698{col 71}{space 3} .2297321
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0197481{col 30}{space 2}  .041746{col 41}{space 1}    0.47{col 50}{space 3}0.636{col 58}{space 4}-.0620725{col 71}{space 3} .1015687
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1644638{col 30}{space 2} .0406247{col 41}{space 1}    4.05{col 50}{space 3}0.000{col 58}{space 4} .0848407{col 71}{space 3} .2440868
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0750757{col 30}{space 2} .0496386{col 41}{space 1}    1.51{col 50}{space 3}0.130{col 58}{space 4}-.0222141{col 71}{space 3} .1723655
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2396506{col 30}{space 2} .0571545{col 41}{space 1}    4.19{col 50}{space 3}0.000{col 58}{space 4} .1276298{col 71}{space 3} .3516715
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2994436{col 30}{space 2} .0434613{col 41}{space 1}    6.89{col 50}{space 3}0.000{col 58}{space 4}  .214261{col 71}{space 3} .3846261
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}  .068658{col 30}{space 2} .0465523{col 41}{space 1}    1.47{col 50}{space 3}0.140{col 58}{space 4} -.022583{col 71}{space 3} .1598989
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} -.003663{col 30}{space 2} .0051975{col 41}{space 1}   -0.70{col 50}{space 3}0.481{col 58}{space 4}-.0138499{col 71}{space 3}  .006524
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .3330388{col 30}{space 2} .0602463{col 41}{space 1}    5.53{col 50}{space 3}0.000{col 58}{space 4} .2149583{col 71}{space 3} .4511194
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0776086{col 30}{space 2}  .056332{col 41}{space 1}    1.38{col 50}{space 3}0.168{col 58}{space 4}-.0328002{col 71}{space 3} .1880173
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .6845126{col 30}{space 2} .0598609{col 41}{space 1}   11.44{col 50}{space 3}0.000{col 58}{space 4} .5671873{col 71}{space 3} .8018378
{txt}electricity_mean {c |}{col 18}{res}{space 2} .7066672{col 30}{space 2} .0616084{col 41}{space 1}   11.47{col 50}{space 3}0.000{col 58}{space 4} .5859169{col 71}{space 3} .8274174
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1029355{col 30}{space 2} .0740987{col 41}{space 1}    1.39{col 50}{space 3}0.165{col 58}{space 4}-.0422952{col 71}{space 3} .2481662
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.0766808{col 30}{space 2} .0550911{col 41}{space 1}   -1.39{col 50}{space 3}0.164{col 58}{space 4}-.1846574{col 71}{space 3} .0312959
{txt}{space 2}pdd9_mean_vill {c |}{col 18}{res}{space 2} .1355826{col 30}{space 2} .0195451{col 41}{space 1}    6.94{col 50}{space 3}0.000{col 58}{space 4}  .097275{col 71}{space 3} .1738903
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.5462053{col 30}{space 2} .0332336{col 41}{space 1}  -16.44{col 50}{space 3}0.000{col 58}{space 4} -.611342{col 71}{space 3}-.4810687
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2}-.5154357{col 30}{space 2} .0336155{col 41}{space 1}  -15.33{col 50}{space 3}0.000{col 58}{space 4}-.5813208{col 71}{space 3}-.4495506
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2}-.3872107{col 30}{space 2} .0336675{col 41}{space 1}  -11.50{col 50}{space 3}0.000{col 58}{space 4}-.4531978{col 71}{space 3}-.3212237
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.568941{col 30}{space 2} .1022116{col 41}{space 1}   44.70{col 50}{space 3}0.000{col 58}{space 4}  4.36861{col 71}{space 3} 4.769272
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .83144873
         {txt}sigma_e {c |} {res} 1.2234985
             {txt}rho {c |} {res} .31591694{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est5
{txt}
{com}. 
. 
. xtreg hdd9  pdd9_vill sum_vill  $xlist  pdd9_mean_vill $year_TANZANIA if country==5, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    11,830
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     5,710

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0145                                         {txt}min = {res}         1
{txt}     between = {res}0.2294                                         {txt}avg = {res}       2.1
{txt}     overall = {res}0.1714                                         {txt}max = {res}         5

                                                {txt}Wald chi2({res}24{txt})     =  {res}  1901.56
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:5,710} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_vill {c |}{col 18}{res}{space 2} .0551174{col 30}{space 2} .0191477{col 41}{space 1}    2.88{col 50}{space 3}0.004{col 58}{space 4} .0175886{col 71}{space 3} .0926461
{txt}{space 8}sum_vill {c |}{col 18}{res}{space 2}-.0477573{col 30}{space 2} .0070618{col 41}{space 1}   -6.76{col 50}{space 3}0.000{col 58}{space 4}-.0615982{col 71}{space 3}-.0339165
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0016467{col 30}{space 2} .0052974{col 41}{space 1}   -0.31{col 50}{space 3}0.756{col 58}{space 4}-.0120295{col 71}{space 3}  .008736
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0533242{col 30}{space 2} .0656373{col 41}{space 1}    0.81{col 50}{space 3}0.417{col 58}{space 4}-.0753224{col 71}{space 3} .1819709
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0013563{col 30}{space 2} .0010463{col 41}{space 1}   -1.30{col 50}{space 3}0.195{col 58}{space 4}-.0034071{col 71}{space 3} .0006945
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0216875{col 30}{space 2} .0370733{col 41}{space 1}    0.58{col 50}{space 3}0.559{col 58}{space 4}-.0509748{col 71}{space 3} .0943498
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2737777{col 30}{space 2} .0353008{col 41}{space 1}    7.76{col 50}{space 3}0.000{col 58}{space 4} .2045893{col 71}{space 3}  .342966
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2730239{col 30}{space 2} .0864213{col 41}{space 1}    3.16{col 50}{space 3}0.002{col 58}{space 4} .1036412{col 71}{space 3} .4424066
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2737047{col 30}{space 2} .0487051{col 41}{space 1}    5.62{col 50}{space 3}0.000{col 58}{space 4} .1782445{col 71}{space 3} .3691649
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0446226{col 30}{space 2} .0561555{col 41}{space 1}    0.79{col 50}{space 3}0.427{col 58}{space 4}-.0654402{col 71}{space 3} .1546854
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}  .125814{col 30}{space 2} .0387829{col 41}{space 1}    3.24{col 50}{space 3}0.001{col 58}{space 4}  .049801{col 71}{space 3} .2018269
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}  .231224{col 30}{space 2} .0407079{col 41}{space 1}    5.68{col 50}{space 3}0.000{col 58}{space 4}  .151438{col 71}{space 3}   .31101
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} -.143467{col 30}{space 2} .0340703{col 41}{space 1}   -4.21{col 50}{space 3}0.000{col 58}{space 4}-.2102436{col 71}{space 3}-.0766904
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0032864{col 30}{space 2} .0030487{col 41}{space 1}    1.08{col 50}{space 3}0.281{col 58}{space 4} -.002689{col 71}{space 3} .0092618
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1223383{col 30}{space 2} .0323731{col 41}{space 1}    3.78{col 50}{space 3}0.000{col 58}{space 4} .0588881{col 71}{space 3} .1857884
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .2688533{col 30}{space 2} .1132883{col 41}{space 1}    2.37{col 50}{space 3}0.018{col 58}{space 4} .0468123{col 71}{space 3} .4908942
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}  .407932{col 30}{space 2} .0664551{col 41}{space 1}    6.14{col 50}{space 3}0.000{col 58}{space 4} .2776825{col 71}{space 3} .5381815
{txt}electricity_mean {c |}{col 18}{res}{space 2} .5547087{col 30}{space 2} .0743284{col 41}{space 1}    7.46{col 50}{space 3}0.000{col 58}{space 4} .4090277{col 71}{space 3} .7003898
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.0113115{col 30}{space 2} .0555256{col 41}{space 1}   -0.20{col 50}{space 3}0.839{col 58}{space 4}-.1201397{col 71}{space 3} .0975166
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .2450324{col 30}{space 2} .0573276{col 41}{space 1}    4.27{col 50}{space 3}0.000{col 58}{space 4} .1326723{col 71}{space 3} .3573925
{txt}{space 2}pdd9_mean_vill {c |}{col 18}{res}{space 2}-.0196454{col 30}{space 2}  .023244{col 41}{space 1}   -0.85{col 50}{space 3}0.398{col 58}{space 4}-.0652027{col 71}{space 3}  .025912
{txt}{space 10}year_1 {c |}{col 18}{res}{space 2}-.0116127{col 30}{space 2} .0377716{col 41}{space 1}   -0.31{col 50}{space 3}0.759{col 58}{space 4}-.0856438{col 71}{space 3} .0624183
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2} .0292403{col 30}{space 2}  .032572{col 41}{space 1}    0.90{col 50}{space 3}0.369{col 58}{space 4}-.0345997{col 71}{space 3} .0930803
{txt}{space 10}year_7 {c |}{col 18}{res}{space 2} .0855304{col 30}{space 2}  .036549{col 41}{space 1}    2.34{col 50}{space 3}0.019{col 58}{space 4} .0138958{col 71}{space 3}  .157165
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.691372{col 30}{space 2} .1080768{col 41}{space 1}   43.41{col 50}{space 3}0.000{col 58}{space 4} 4.479545{col 71}{space 3} 4.903198
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .76283151
         {txt}sigma_e {c |} {res} 1.2279711
             {txt}rho {c |} {res} .27845009{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est6
{txt}
{com}. 
. 
. xtreg hdd9  pdd9_vill sum_vill  $xlist  pdd9_mean_vill $year_UGANDA if country==4, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    16,114
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     4,402

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0420                                         {txt}min = {res}         1
{txt}     between = {res}0.2855                                         {txt}avg = {res}       3.7
{txt}     overall = {res}0.1916                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}26{txt})     =  {res}  2534.12
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:4,402} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_vill {c |}{col 18}{res}{space 2} .0199183{col 30}{space 2} .0133128{col 41}{space 1}    1.50{col 50}{space 3}0.135{col 58}{space 4}-.0061743{col 71}{space 3}  .046011
{txt}{space 8}sum_vill {c |}{col 18}{res}{space 2} -.030819{col 30}{space 2} .0047062{col 41}{space 1}   -6.55{col 50}{space 3}0.000{col 58}{space 4} -.040043{col 71}{space 3}-.0215951
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}  .025645{col 30}{space 2} .0054645{col 41}{space 1}    4.69{col 50}{space 3}0.000{col 58}{space 4} .0149347{col 71}{space 3} .0363552
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0531743{col 30}{space 2} .0602836{col 41}{space 1}    0.88{col 50}{space 3}0.378{col 58}{space 4}-.0649794{col 71}{space 3}  .171328
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0010848{col 30}{space 2} .0010181{col 41}{space 1}   -1.07{col 50}{space 3}0.287{col 58}{space 4}-.0030803{col 71}{space 3} .0009107
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}   .04709{col 30}{space 2} .0343335{col 41}{space 1}    1.37{col 50}{space 3}0.170{col 58}{space 4}-.0202025{col 71}{space 3} .1143825
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3243791{col 30}{space 2} .0337351{col 41}{space 1}    9.62{col 50}{space 3}0.000{col 58}{space 4} .2582594{col 71}{space 3} .3904987
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2354538{col 30}{space 2} .0563473{col 41}{space 1}    4.18{col 50}{space 3}0.000{col 58}{space 4} .1250151{col 71}{space 3} .3458925
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2496645{col 30}{space 2} .0374903{col 41}{space 1}    6.66{col 50}{space 3}0.000{col 58}{space 4} .1761848{col 71}{space 3} .3231441
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}    .3365{col 30}{space 2} .0378888{col 41}{space 1}    8.88{col 50}{space 3}0.000{col 58}{space 4} .2622394{col 71}{space 3} .4107607
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0370737{col 30}{space 2} .0305793{col 41}{space 1}    1.21{col 50}{space 3}0.225{col 58}{space 4}-.0228607{col 71}{space 3}  .097008
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2046684{col 30}{space 2} .0321477{col 41}{space 1}    6.37{col 50}{space 3}0.000{col 58}{space 4} .1416599{col 71}{space 3} .2676768
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} .0092233{col 30}{space 2} .0249723{col 41}{space 1}    0.37{col 50}{space 3}0.712{col 58}{space 4}-.0397216{col 71}{space 3} .0581681
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0016156{col 30}{space 2} .0017395{col 41}{space 1}    0.93{col 50}{space 3}0.353{col 58}{space 4}-.0017937{col 71}{space 3} .0050249
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0508888{col 30}{space 2} .0277693{col 41}{space 1}    1.83{col 50}{space 3}0.067{col 58}{space 4} -.003538{col 71}{space 3} .1053156
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1395907{col 30}{space 2} .0870131{col 41}{space 1}    1.60{col 50}{space 3}0.109{col 58}{space 4}-.0309519{col 71}{space 3} .3101333
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .3471975{col 30}{space 2}  .062166{col 41}{space 1}    5.59{col 50}{space 3}0.000{col 58}{space 4} .2253545{col 71}{space 3} .4690405
{txt}electricity_mean {c |}{col 18}{res}{space 2} .3740562{col 30}{space 2} .0688118{col 41}{space 1}    5.44{col 50}{space 3}0.000{col 58}{space 4} .2391875{col 71}{space 3} .5089249
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1121482{col 30}{space 2} .0551921{col 41}{space 1}    2.03{col 50}{space 3}0.042{col 58}{space 4} .0039737{col 71}{space 3} .2203226
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .3036198{col 30}{space 2} .0536368{col 41}{space 1}    5.66{col 50}{space 3}0.000{col 58}{space 4} .1984935{col 71}{space 3}  .408746
{txt}{space 2}pdd9_mean_vill {c |}{col 18}{res}{space 2} .1852284{col 30}{space 2} .0217363{col 41}{space 1}    8.52{col 50}{space 3}0.000{col 58}{space 4}  .142626{col 71}{space 3} .2278308
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.1259459{col 30}{space 2} .0384392{col 41}{space 1}   -3.28{col 50}{space 3}0.001{col 58}{space 4}-.2012854{col 71}{space 3}-.0506065
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2}-.0407199{col 30}{space 2} .0340009{col 41}{space 1}   -1.20{col 50}{space 3}0.231{col 58}{space 4}-.1073604{col 71}{space 3} .0259206
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .3514356{col 30}{space 2} .0346141{col 41}{space 1}   10.15{col 50}{space 3}0.000{col 58}{space 4} .2835932{col 71}{space 3}  .419278
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2} .1041186{col 30}{space 2} .0343085{col 41}{space 1}    3.03{col 50}{space 3}0.002{col 58}{space 4} .0368752{col 71}{space 3}  .171362
{txt}{space 9}year_10 {c |}{col 18}{res}{space 2} .2975213{col 30}{space 2} .0320754{col 41}{space 1}    9.28{col 50}{space 3}0.000{col 58}{space 4} .2346547{col 71}{space 3}  .360388
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 3.277769{col 30}{space 2}  .127035{col 41}{space 1}   25.80{col 50}{space 3}0.000{col 58}{space 4} 3.028785{col 71}{space 3} 3.526753
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .79554545
         {txt}sigma_e {c |} {res} 1.2677833
             {txt}rho {c |} {res} .28252027{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est7
{txt}
{com}. esttab using  S7.rtf, se replace star(* 0.1 ** 0.05 *** 0.01) cells (b(star fmt(%9.3f)) se (par(( )) fmt(%9.3f)))  stats(N r2_b  r2_w r2_o p, fmt(%4.0f %4.3f %4.3f %6.3f)) keep(pdd9_vill    $xlist  pdd9_mean_vill sum_vill _cons)
{res}{txt}(note: file S7.rtf not found)
(output written to {browse  `"S7.rtf"'})

{com}. 
. 
. ********************************************************************************
. *                                Table S8                                      *
. ********************************************************************************
. eststo clear
{txt}
{com}. xtreg hdd9  pdd9_town sum_town  $xlist  pdd9_mean_town i.country i.year   , cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    65,579
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}    27,229

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0230                                         {txt}min = {res}         1
{txt}     between = {res}0.3659                                         {txt}avg = {res}       2.4
{txt}     overall = {res}0.2832                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}36{txt})     =  {res} 20269.46
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:27,229} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_town {c |}{col 18}{res}{space 2}  .024555{col 30}{space 2} .0073425{col 41}{space 1}    3.34{col 50}{space 3}0.001{col 58}{space 4}  .010164{col 71}{space 3}  .038946
{txt}{space 8}sum_town {c |}{col 18}{res}{space 2}-.0017515{col 30}{space 2} .0002209{col 41}{space 1}   -7.93{col 50}{space 3}0.000{col 58}{space 4}-.0021845{col 71}{space 3}-.0013184
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0016164{col 30}{space 2} .0024382{col 41}{space 1}    0.66{col 50}{space 3}0.507{col 58}{space 4}-.0031624{col 71}{space 3} .0063953
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0353018{col 30}{space 2} .0277299{col 41}{space 1}    1.27{col 50}{space 3}0.203{col 58}{space 4}-.0190478{col 71}{space 3} .0896514
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0005458{col 30}{space 2} .0004634{col 41}{space 1}    1.18{col 50}{space 3}0.239{col 58}{space 4}-.0003625{col 71}{space 3} .0014542
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0476093{col 30}{space 2} .0169331{col 41}{space 1}    2.81{col 50}{space 3}0.005{col 58}{space 4}  .014421{col 71}{space 3} .0807975
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3060074{col 30}{space 2} .0148137{col 41}{space 1}   20.66{col 50}{space 3}0.000{col 58}{space 4} .2769731{col 71}{space 3} .3350417
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}  .126764{col 30}{space 2} .0294804{col 41}{space 1}    4.30{col 50}{space 3}0.000{col 58}{space 4} .0689836{col 71}{space 3} .1845444
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1769806{col 30}{space 2}  .019319{col 41}{space 1}    9.16{col 50}{space 3}0.000{col 58}{space 4} .1391162{col 71}{space 3} .2148451
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1497898{col 30}{space 2} .0228068{col 41}{space 1}    6.57{col 50}{space 3}0.000{col 58}{space 4} .1050893{col 71}{space 3} .1944903
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1281352{col 30}{space 2} .0199232{col 41}{space 1}    6.43{col 50}{space 3}0.000{col 58}{space 4} .0890866{col 71}{space 3} .1671839
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2177776{col 30}{space 2}  .018309{col 41}{space 1}   11.89{col 50}{space 3}0.000{col 58}{space 4} .1818927{col 71}{space 3} .2536625
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} -.052856{col 30}{space 2} .0142538{col 41}{space 1}   -3.71{col 50}{space 3}0.000{col 58}{space 4}-.0807929{col 71}{space 3} -.024919
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0001995{col 30}{space 2} .0011021{col 41}{space 1}    0.18{col 50}{space 3}0.856{col 58}{space 4}-.0019607{col 71}{space 3} .0023596
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}  .155978{col 30}{space 2} .0160538{col 41}{space 1}    9.72{col 50}{space 3}0.000{col 58}{space 4} .1245132{col 71}{space 3} .1874428
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0292711{col 30}{space 2} .0396366{col 41}{space 1}    0.74{col 50}{space 3}0.460{col 58}{space 4}-.0484152{col 71}{space 3} .1069573
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .5539139{col 30}{space 2}  .028099{col 41}{space 1}   19.71{col 50}{space 3}0.000{col 58}{space 4} .4988409{col 71}{space 3} .6089869
{txt}electricity_mean {c |}{col 18}{res}{space 2} .6845201{col 30}{space 2}  .030759{col 41}{space 1}   22.25{col 50}{space 3}0.000{col 58}{space 4} .6242335{col 71}{space 3} .7448067
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1703215{col 30}{space 2} .0294106{col 41}{space 1}    5.79{col 50}{space 3}0.000{col 58}{space 4} .1126778{col 71}{space 3} .2279652
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}  .148127{col 30}{space 2} .0255564{col 41}{space 1}    5.80{col 50}{space 3}0.000{col 58}{space 4} .0980373{col 71}{space 3} .1982167
{txt}{space 2}pdd9_mean_town {c |}{col 18}{res}{space 2} .0831302{col 30}{space 2} .0094012{col 41}{space 1}    8.84{col 50}{space 3}0.000{col 58}{space 4} .0647041{col 71}{space 3} .1015563
{txt}{space 16} {c |}
{space 9}country {c |}
{space 8}Nigeria  {c |}{col 18}{res}{space 2}-.3504199{col 30}{space 2} .0346934{col 41}{space 1}  -10.10{col 50}{space 3}0.000{col 58}{space 4}-.4184177{col 71}{space 3}-.2824222
{txt}{space 7}Ethiopia  {c |}{col 18}{res}{space 2}-1.569396{col 30}{space 2} .0336568{col 41}{space 1}  -46.63{col 50}{space 3}0.000{col 58}{space 4}-1.635362{col 71}{space 3} -1.50343
{txt}{space 9}Uganda  {c |}{col 18}{res}{space 2}-.5278385{col 30}{space 2} .0340999{col 41}{space 1}  -15.48{col 50}{space 3}0.000{col 58}{space 4}-.5946731{col 71}{space 3}-.4610039
{txt}{space 7}Tanzania  {c |}{col 18}{res}{space 2}-.3160157{col 30}{space 2} .0342103{col 41}{space 1}   -9.24{col 50}{space 3}0.000{col 58}{space 4}-.3830666{col 71}{space 3}-.2489648
{txt}{space 9}Malawi  {c |}{col 18}{res}{space 2} .3591224{col 30}{space 2} .0432505{col 41}{space 1}    8.30{col 50}{space 3}0.000{col 58}{space 4} .2743529{col 71}{space 3} .4438918
{txt}{space 16} {c |}
{space 12}year {c |}
{space 11}2009  {c |}{col 18}{res}{space 2}-.2385168{col 30}{space 2} .0463843{col 41}{space 1}   -5.14{col 50}{space 3}0.000{col 58}{space 4}-.3294284{col 71}{space 3}-.1476052
{txt}{space 11}2010  {c |}{col 18}{res}{space 2} .0095335{col 30}{space 2} .0351702{col 41}{space 1}    0.27{col 50}{space 3}0.786{col 58}{space 4}-.0593989{col 71}{space 3} .0784659
{txt}{space 11}2011  {c |}{col 18}{res}{space 2} .0300469{col 30}{space 2} .0388651{col 41}{space 1}    0.77{col 50}{space 3}0.439{col 58}{space 4}-.0461272{col 71}{space 3} .1062211
{txt}{space 11}2012  {c |}{col 18}{res}{space 2} .0126483{col 30}{space 2} .0357017{col 41}{space 1}    0.35{col 50}{space 3}0.723{col 58}{space 4}-.0573257{col 71}{space 3} .0826224
{txt}{space 11}2013  {c |}{col 18}{res}{space 2} .1110819{col 30}{space 2}  .039333{col 41}{space 1}    2.82{col 50}{space 3}0.005{col 58}{space 4} .0339907{col 71}{space 3}  .188173
{txt}{space 11}2014  {c |}{col 18}{res}{space 2}-.0936021{col 30}{space 2} .0395287{col 41}{space 1}   -2.37{col 50}{space 3}0.018{col 58}{space 4} -.171077{col 71}{space 3}-.0161273
{txt}{space 11}2015  {c |}{col 18}{res}{space 2} .1703518{col 30}{space 2} .0381182{col 41}{space 1}    4.47{col 50}{space 3}0.000{col 58}{space 4} .0956415{col 71}{space 3} .2450621
{txt}{space 11}2016  {c |}{col 18}{res}{space 2}-.2216465{col 30}{space 2} .0587194{col 41}{space 1}   -3.77{col 50}{space 3}0.000{col 58}{space 4}-.3367344{col 71}{space 3}-.1065586
{txt}{space 11}2018  {c |}{col 18}{res}{space 2} .4205357{col 30}{space 2} .0401217{col 41}{space 1}   10.48{col 50}{space 3}0.000{col 58}{space 4} .3418987{col 71}{space 3} .4991727
{txt}{space 11}2019  {c |}{col 18}{res}{space 2}-.0170279{col 30}{space 2}  .039106{col 41}{space 1}   -0.44{col 50}{space 3}0.663{col 58}{space 4}-.0936744{col 71}{space 3} .0596185
{txt}{space 16} {c |}
{space 11}_cons {c |}{col 18}{res}{space 2} 4.113824{col 30}{space 2} .0622117{col 41}{space 1}   66.13{col 50}{space 3}0.000{col 58}{space 4} 3.991891{col 71}{space 3} 4.235757
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .79816042
         {txt}sigma_e {c |} {res} 1.2370778
             {txt}rho {c |} {res}  .2939253{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est1
{txt}
{com}. 
. xtreg hdd9  pdd9_town sum_town  $xlist  pdd9_mean_town $year_ETHIOPIA if country==3, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    11,410
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     4,555

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0213                                         {txt}min = {res}         1
{txt}     between = {res}0.3343                                         {txt}avg = {res}       2.5
{txt}     overall = {res}0.2247                                         {txt}max = {res}         3

                                                {txt}Wald chi2({res}22{txt})     =  {res}  2483.50
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:4,555} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_town {c |}{col 18}{res}{space 2} .0544296{col 30}{space 2} .0158992{col 41}{space 1}    3.42{col 50}{space 3}0.001{col 58}{space 4} .0232679{col 71}{space 3} .0855914
{txt}{space 8}sum_town {c |}{col 18}{res}{space 2}-.0056712{col 30}{space 2} .0006116{col 41}{space 1}   -9.27{col 50}{space 3}0.000{col 58}{space 4}-.0068698{col 71}{space 3}-.0044726
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0503228{col 30}{space 2} .0070227{col 41}{space 1}    7.17{col 50}{space 3}0.000{col 58}{space 4} .0365585{col 71}{space 3}  .064087
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0624082{col 30}{space 2} .0573747{col 41}{space 1}   -1.09{col 50}{space 3}0.277{col 58}{space 4}-.1748605{col 71}{space 3} .0500442
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} -.003466{col 30}{space 2} .0009883{col 41}{space 1}   -3.51{col 50}{space 3}0.000{col 58}{space 4}-.0054031{col 71}{space 3}-.0015289
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0529192{col 30}{space 2} .0357638{col 41}{space 1}   -1.48{col 50}{space 3}0.139{col 58}{space 4}-.1230149{col 71}{space 3} .0171766
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3687682{col 30}{space 2} .0313347{col 41}{space 1}   11.77{col 50}{space 3}0.000{col 58}{space 4} .3073533{col 71}{space 3}  .430183
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}-.2110038{col 30}{space 2} .1571486{col 41}{space 1}   -1.34{col 50}{space 3}0.179{col 58}{space 4}-.5190093{col 71}{space 3} .0970018
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1807972{col 30}{space 2} .0377411{col 41}{space 1}    4.79{col 50}{space 3}0.000{col 58}{space 4}  .106826{col 71}{space 3} .2547684
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1633286{col 30}{space 2} .0460337{col 41}{space 1}    3.55{col 50}{space 3}0.000{col 58}{space 4} .0731041{col 71}{space 3} .2535531
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0782836{col 30}{space 2} .0632242{col 41}{space 1}    1.24{col 50}{space 3}0.216{col 58}{space 4}-.0456336{col 71}{space 3} .2022008
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2214184{col 30}{space 2} .0499538{col 41}{space 1}    4.43{col 50}{space 3}0.000{col 58}{space 4} .1235108{col 71}{space 3}  .319326
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1161477{col 30}{space 2} .0295255{col 41}{space 1}   -3.93{col 50}{space 3}0.000{col 58}{space 4}-.1740166{col 71}{space 3}-.0582788
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0123207{col 30}{space 2} .0035941{col 41}{space 1}    3.43{col 50}{space 3}0.001{col 58}{space 4} .0052764{col 71}{space 3} .0193649
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .2676345{col 30}{space 2} .0310055{col 41}{space 1}    8.63{col 50}{space 3}0.000{col 58}{space 4} .2068648{col 71}{space 3} .3284041
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .9553488{col 30}{space 2}  .261049{col 41}{space 1}    3.66{col 50}{space 3}0.000{col 58}{space 4} .4437021{col 71}{space 3} 1.466996
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .4631296{col 30}{space 2} .0568723{col 41}{space 1}    8.14{col 50}{space 3}0.000{col 58}{space 4} .3516619{col 71}{space 3} .5745973
{txt}electricity_mean {c |}{col 18}{res}{space 2} .5184451{col 30}{space 2} .0670629{col 41}{space 1}    7.73{col 50}{space 3}0.000{col 58}{space 4} .3870043{col 71}{space 3} .6498858
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .4502796{col 30}{space 2} .0971828{col 41}{space 1}    4.63{col 50}{space 3}0.000{col 58}{space 4} .2598049{col 71}{space 3} .6407543
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .1009689{col 30}{space 2} .0634125{col 41}{space 1}    1.59{col 50}{space 3}0.111{col 58}{space 4}-.0233174{col 71}{space 3} .2252552
{txt}{space 2}pdd9_mean_town {c |}{col 18}{res}{space 2} .0490843{col 30}{space 2} .0193443{col 41}{space 1}    2.54{col 50}{space 3}0.011{col 58}{space 4} .0111703{col 71}{space 3} .0869984
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}-.1373436{col 30}{space 2} .0220914{col 41}{space 1}   -6.22{col 50}{space 3}0.000{col 58}{space 4}-.1806421{col 71}{space 3}-.0940452
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}  2.81016{col 30}{space 2}  .093887{col 41}{space 1}   29.93{col 50}{space 3}0.000{col 58}{space 4} 2.626145{col 71}{space 3} 2.994175
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .73031715
         {txt}sigma_e {c |} {res} 1.0776877
             {txt}rho {c |} {res} .31471049{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est2
{txt}
{com}. 
. xtreg hdd9  pdd9_town sum_town  $xlist  pdd9_mean_town $year_MALAWI  if country==6, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     4,626
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     1,571

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0215                                         {txt}min = {res}         1
{txt}     between = {res}0.3908                                         {txt}avg = {res}       2.9
{txt}     overall = {res}0.2755                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}23{txt})     =  {res}  1555.06
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:1,571} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_town {c |}{col 18}{res}{space 2} .0354293{col 30}{space 2} .0264804{col 41}{space 1}    1.34{col 50}{space 3}0.181{col 58}{space 4}-.0164712{col 71}{space 3} .0873299
{txt}{space 8}sum_town {c |}{col 18}{res}{space 2}-.0133754{col 30}{space 2} .0035136{col 41}{space 1}   -3.81{col 50}{space 3}0.000{col 58}{space 4} -.020262{col 71}{space 3}-.0064889
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0008839{col 30}{space 2} .0111509{col 41}{space 1}   -0.08{col 50}{space 3}0.937{col 58}{space 4}-.0227393{col 71}{space 3} .0209715
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.2563241{col 30}{space 2} .1031917{col 41}{space 1}   -2.48{col 50}{space 3}0.013{col 58}{space 4}-.4585762{col 71}{space 3} -.054072
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0013399{col 30}{space 2} .0017073{col 41}{space 1}   -0.78{col 50}{space 3}0.433{col 58}{space 4}-.0046861{col 71}{space 3} .0020062
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0905517{col 30}{space 2} .0600314{col 41}{space 1}   -1.51{col 50}{space 3}0.131{col 58}{space 4}-.2082112{col 71}{space 3} .0271077
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3133136{col 30}{space 2} .0585335{col 41}{space 1}    5.35{col 50}{space 3}0.000{col 58}{space 4}   .19859{col 71}{space 3} .4280372
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2609138{col 30}{space 2} .1918045{col 41}{space 1}    1.36{col 50}{space 3}0.174{col 58}{space 4}-.1150161{col 71}{space 3} .6368436
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1058968{col 30}{space 2} .0695855{col 41}{space 1}    1.52{col 50}{space 3}0.128{col 58}{space 4}-.0304882{col 71}{space 3} .2422818
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1962309{col 30}{space 2}  .140157{col 41}{space 1}    1.40{col 50}{space 3}0.161{col 58}{space 4}-.0784717{col 71}{space 3} .4709335
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1341625{col 30}{space 2} .0811883{col 41}{space 1}    1.65{col 50}{space 3}0.098{col 58}{space 4}-.0249636{col 71}{space 3} .2932886
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}  .252835{col 30}{space 2} .0561609{col 41}{space 1}    4.50{col 50}{space 3}0.000{col 58}{space 4} .1427618{col 71}{space 3} .3629083
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1458804{col 30}{space 2} .0434658{col 41}{space 1}   -3.36{col 50}{space 3}0.001{col 58}{space 4}-.2310717{col 71}{space 3}-.0606891
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0988282{col 30}{space 2} .0347636{col 41}{space 1}    2.84{col 50}{space 3}0.004{col 58}{space 4} .0306929{col 71}{space 3} .1669635
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0927883{col 30}{space 2} .0621989{col 41}{space 1}    1.49{col 50}{space 3}0.136{col 58}{space 4}-.0291193{col 71}{space 3} .2146959
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0771413{col 30}{space 2} .3271422{col 41}{space 1}    0.24{col 50}{space 3}0.814{col 58}{space 4}-.5640457{col 71}{space 3} .7183283
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .7097562{col 30}{space 2} .1090171{col 41}{space 1}    6.51{col 50}{space 3}0.000{col 58}{space 4} .4960866{col 71}{space 3} .9234258
{txt}electricity_mean {c |}{col 18}{res}{space 2} .8368963{col 30}{space 2} .1765777{col 41}{space 1}    4.74{col 50}{space 3}0.000{col 58}{space 4} .4908105{col 71}{space 3} 1.182982
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .3303057{col 30}{space 2} .1145612{col 41}{space 1}    2.88{col 50}{space 3}0.004{col 58}{space 4} .1057699{col 71}{space 3} .5548416
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .2698569{col 30}{space 2} .1002771{col 41}{space 1}    2.69{col 50}{space 3}0.007{col 58}{space 4} .0733173{col 71}{space 3} .4663965
{txt}{space 2}pdd9_mean_town {c |}{col 18}{res}{space 2}-.0372205{col 30}{space 2} .0393211{col 41}{space 1}   -0.95{col 50}{space 3}0.344{col 58}{space 4}-.1142883{col 71}{space 3} .0398474
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2} .2618285{col 30}{space 2} .0559477{col 41}{space 1}    4.68{col 50}{space 3}0.000{col 58}{space 4}  .152173{col 71}{space 3} .3714839
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}  .111046{col 30}{space 2} .0497797{col 41}{space 1}    2.23{col 50}{space 3}0.026{col 58}{space 4} .0134796{col 71}{space 3} .2086124
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 5.262093{col 30}{space 2}  .222422{col 41}{space 1}   23.66{col 50}{space 3}0.000{col 58}{space 4} 4.826154{col 71}{space 3} 5.698032
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .70045639
         {txt}sigma_e {c |} {res} 1.2904676
             {txt}rho {c |} {res}  .2275749{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est3
{txt}
{com}. 
. xtreg hdd9 pdd9_town sum_town  $xlist  pdd9_mean_town $year_NIGER if country==1, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     6,536
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     3,837

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0258                                         {txt}min = {res}         1
{txt}     between = {res}0.2263                                         {txt}avg = {res}       1.7
{txt}     overall = {res}0.1735                                         {txt}max = {res}         2

                                                {txt}Wald chi2({res}22{txt})     =  {res}  1391.18
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,837} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_town {c |}{col 18}{res}{space 2} .0795844{col 30}{space 2} .0299892{col 41}{space 1}    2.65{col 50}{space 3}0.008{col 58}{space 4} .0208066{col 71}{space 3} .1383622
{txt}{space 8}sum_town {c |}{col 18}{res}{space 2}-.0014016{col 30}{space 2} .0003267{col 41}{space 1}   -4.29{col 50}{space 3}0.000{col 58}{space 4}-.0020419{col 71}{space 3}-.0007612
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0112542{col 30}{space 2} .0064052{col 41}{space 1}    1.76{col 50}{space 3}0.079{col 58}{space 4}-.0012998{col 71}{space 3} .0238081
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} -.144688{col 30}{space 2} .0992959{col 41}{space 1}   -1.46{col 50}{space 3}0.145{col 58}{space 4}-.3393043{col 71}{space 3} .0499284
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0032267{col 30}{space 2}   .00142{col 41}{space 1}    2.27{col 50}{space 3}0.023{col 58}{space 4} .0004435{col 71}{space 3}   .00601
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0962279{col 30}{space 2} .0588911{col 41}{space 1}    1.63{col 50}{space 3}0.102{col 58}{space 4}-.0191965{col 71}{space 3} .2116524
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3536739{col 30}{space 2} .0461326{col 41}{space 1}    7.67{col 50}{space 3}0.000{col 58}{space 4} .2632558{col 71}{space 3} .4440921
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}  .338598{col 30}{space 2} .1116514{col 41}{space 1}    3.03{col 50}{space 3}0.002{col 58}{space 4} .1197653{col 71}{space 3} .5574306
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1150273{col 30}{space 2} .0786894{col 41}{space 1}    1.46{col 50}{space 3}0.144{col 58}{space 4} -.039201{col 71}{space 3} .2692556
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .2636178{col 30}{space 2} .1251279{col 41}{space 1}    2.11{col 50}{space 3}0.035{col 58}{space 4} .0183717{col 71}{space 3} .5088639
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2104011{col 30}{space 2} .0909576{col 41}{space 1}    2.31{col 50}{space 3}0.021{col 58}{space 4} .0321275{col 71}{space 3} .3886747
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}-.1609286{col 30}{space 2} .0698679{col 41}{space 1}   -2.30{col 50}{space 3}0.021{col 58}{space 4}-.2978672{col 71}{space 3}-.0239901
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1416447{col 30}{space 2} .0450748{col 41}{space 1}   -3.14{col 50}{space 3}0.002{col 58}{space 4}-.2299897{col 71}{space 3}-.0532996
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0017266{col 30}{space 2} .0015604{col 41}{space 1}   -1.11{col 50}{space 3}0.269{col 58}{space 4}-.0047848{col 71}{space 3} .0013317
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .2147425{col 30}{space 2} .2161232{col 41}{space 1}    0.99{col 50}{space 3}0.320{col 58}{space 4}-.2088512{col 71}{space 3} .6383361
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0093779{col 30}{space 2} .1340446{col 41}{space 1}    0.07{col 50}{space 3}0.944{col 58}{space 4}-.2533446{col 71}{space 3} .2721005
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .2901944{col 30}{space 2} .0962768{col 41}{space 1}    3.01{col 50}{space 3}0.003{col 58}{space 4} .1014952{col 71}{space 3} .4788935
{txt}electricity_mean {c |}{col 18}{res}{space 2} .5113504{col 30}{space 2} .1412556{col 41}{space 1}    3.62{col 50}{space 3}0.000{col 58}{space 4} .2344946{col 71}{space 3} .7882063
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}  .179261{col 30}{space 2} .1114683{col 41}{space 1}    1.61{col 50}{space 3}0.108{col 58}{space 4}-.0392128{col 71}{space 3} .3977348
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .4040704{col 30}{space 2} .0852851{col 41}{space 1}    4.74{col 50}{space 3}0.000{col 58}{space 4} .2369146{col 71}{space 3} .5712262
{txt}{space 2}pdd9_mean_town {c |}{col 18}{res}{space 2}  .048287{col 30}{space 2} .0365711{col 41}{space 1}    1.32{col 50}{space 3}0.187{col 58}{space 4} -.023391{col 71}{space 3}  .119965
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2} .2499507{col 30}{space 2} .0391397{col 41}{space 1}    6.39{col 50}{space 3}0.000{col 58}{space 4} .1732383{col 71}{space 3}  .326663
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 3.948392{col 30}{space 2} .1467919{col 41}{space 1}   26.90{col 50}{space 3}0.000{col 58}{space 4} 3.660685{col 71}{space 3} 4.236099
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .55335731
         {txt}sigma_e {c |} {res} 1.3965162
             {txt}rho {c |} {res} .13570109{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est4
{txt}
{com}. 
. 
. xtreg hdd9  pdd9_town sum_town  $xlist  pdd9_mean_town $year_NIGERIA if country==2, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    15,063
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     7,154

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0355                                         {txt}min = {res}         1
{txt}     between = {res}0.3122                                         {txt}avg = {res}       2.1
{txt}     overall = {res}0.2659                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}24{txt})     =  {res}  4233.22
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:7,154} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_town {c |}{col 18}{res}{space 2} .0667879{col 30}{space 2} .0151278{col 41}{space 1}    4.41{col 50}{space 3}0.000{col 58}{space 4} .0371379{col 71}{space 3} .0964379
{txt}{space 8}sum_town {c |}{col 18}{res}{space 2}-.0192483{col 30}{space 2} .0025452{col 41}{space 1}   -7.56{col 50}{space 3}0.000{col 58}{space 4}-.0242367{col 71}{space 3}-.0142599
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0200674{col 30}{space 2} .0046374{col 41}{space 1}   -4.33{col 50}{space 3}0.000{col 58}{space 4}-.0291564{col 71}{space 3}-.0109784
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}  .155521{col 30}{space 2}  .053633{col 41}{space 1}    2.90{col 50}{space 3}0.004{col 58}{space 4} .0504022{col 71}{space 3} .2606398
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}  .003644{col 30}{space 2} .0009645{col 41}{space 1}    3.78{col 50}{space 3}0.000{col 58}{space 4} .0017537{col 71}{space 3} .0055343
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .2851424{col 30}{space 2} .0390102{col 41}{space 1}    7.31{col 50}{space 3}0.000{col 58}{space 4} .2086838{col 71}{space 3}  .361601
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .1812109{col 30}{space 2} .0284207{col 41}{space 1}    6.38{col 50}{space 3}0.000{col 58}{space 4} .1255073{col 71}{space 3} .2369146
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0157132{col 30}{space 2} .0417953{col 41}{space 1}    0.38{col 50}{space 3}0.707{col 58}{space 4}-.0662041{col 71}{space 3} .0976305
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1671488{col 30}{space 2}  .040623{col 41}{space 1}    4.11{col 50}{space 3}0.000{col 58}{space 4} .0875293{col 71}{space 3} .2467684
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0749593{col 30}{space 2} .0494861{col 41}{space 1}    1.51{col 50}{space 3}0.130{col 58}{space 4}-.0220317{col 71}{space 3} .1719502
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2458455{col 30}{space 2} .0570914{col 41}{space 1}    4.31{col 50}{space 3}0.000{col 58}{space 4} .1339485{col 71}{space 3} .3577425
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .3063778{col 30}{space 2} .0434631{col 41}{space 1}    7.05{col 50}{space 3}0.000{col 58}{space 4} .2211917{col 71}{space 3}  .391564
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} .0485843{col 30}{space 2} .0467535{col 41}{space 1}    1.04{col 50}{space 3}0.299{col 58}{space 4}-.0430509{col 71}{space 3} .1402195
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} -.005316{col 30}{space 2} .0059406{col 41}{space 1}   -0.89{col 50}{space 3}0.371{col 58}{space 4}-.0169594{col 71}{space 3} .0063274
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .3363599{col 30}{space 2} .0604133{col 41}{space 1}    5.57{col 50}{space 3}0.000{col 58}{space 4}  .217952{col 71}{space 3} .4547678
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0482978{col 30}{space 2} .0565675{col 41}{space 1}    0.85{col 50}{space 3}0.393{col 58}{space 4}-.0625723{col 71}{space 3}  .159168
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .7352137{col 30}{space 2} .0597581{col 41}{space 1}   12.30{col 50}{space 3}0.000{col 58}{space 4} .6180899{col 71}{space 3} .8523375
{txt}electricity_mean {c |}{col 18}{res}{space 2} .8144564{col 30}{space 2} .0610692{col 41}{space 1}   13.34{col 50}{space 3}0.000{col 58}{space 4} .6947629{col 71}{space 3} .9341498
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1579555{col 30}{space 2} .0739629{col 41}{space 1}    2.14{col 50}{space 3}0.033{col 58}{space 4} .0129909{col 71}{space 3} .3029201
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.0465711{col 30}{space 2} .0552215{col 41}{space 1}   -0.84{col 50}{space 3}0.399{col 58}{space 4}-.1548032{col 71}{space 3}  .061661
{txt}{space 2}pdd9_mean_town {c |}{col 18}{res}{space 2} .1157861{col 30}{space 2} .0193973{col 41}{space 1}    5.97{col 50}{space 3}0.000{col 58}{space 4} .0777681{col 71}{space 3} .1538041
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.5581672{col 30}{space 2} .0342242{col 41}{space 1}  -16.31{col 50}{space 3}0.000{col 58}{space 4}-.6252454{col 71}{space 3} -.491089
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2}-.5082787{col 30}{space 2} .0346153{col 41}{space 1}  -14.68{col 50}{space 3}0.000{col 58}{space 4}-.5761234{col 71}{space 3}-.4404341
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2}-.3663143{col 30}{space 2} .0346864{col 41}{space 1}  -10.56{col 50}{space 3}0.000{col 58}{space 4}-.4342984{col 71}{space 3}-.2983302
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 3.977114{col 30}{space 2} .0933887{col 41}{space 1}   42.59{col 50}{space 3}0.000{col 58}{space 4} 3.794075{col 71}{space 3} 4.160152
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .84623051
         {txt}sigma_e {c |} {res} 1.2232495
             {txt}rho {c |} {res} .32367174{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est5
{txt}
{com}. 
. 
. xtreg hdd9  pdd9_town sum_town  $xlist  pdd9_mean_town $year_TANZANIA if country==5, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    11,830
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     5,710

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0130                                         {txt}min = {res}         1
{txt}     between = {res}0.2246                                         {txt}avg = {res}       2.1
{txt}     overall = {res}0.1685                                         {txt}max = {res}         5

                                                {txt}Wald chi2({res}24{txt})     =  {res}  1860.45
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:5,710} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_town {c |}{col 18}{res}{space 2}-.0002759{col 30}{space 2} .0209966{col 41}{space 1}   -0.01{col 50}{space 3}0.990{col 58}{space 4}-.0414285{col 71}{space 3} .0408767
{txt}{space 8}sum_town {c |}{col 18}{res}{space 2}-.0137397{col 30}{space 2} .0045708{col 41}{space 1}   -3.01{col 50}{space 3}0.003{col 58}{space 4}-.0226982{col 71}{space 3}-.0047812
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0013187{col 30}{space 2} .0052992{col 41}{space 1}   -0.25{col 50}{space 3}0.803{col 58}{space 4}-.0117049{col 71}{space 3} .0090674
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0518961{col 30}{space 2} .0656271{col 41}{space 1}    0.79{col 50}{space 3}0.429{col 58}{space 4}-.0767305{col 71}{space 3} .1805228
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0013316{col 30}{space 2} .0010466{col 41}{space 1}   -1.27{col 50}{space 3}0.203{col 58}{space 4}-.0033829{col 71}{space 3} .0007197
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0213531{col 30}{space 2} .0372256{col 41}{space 1}    0.57{col 50}{space 3}0.566{col 58}{space 4}-.0516078{col 71}{space 3}  .094314
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2786661{col 30}{space 2} .0353176{col 41}{space 1}    7.89{col 50}{space 3}0.000{col 58}{space 4} .2094448{col 71}{space 3} .3478873
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2617608{col 30}{space 2} .0864074{col 41}{space 1}    3.03{col 50}{space 3}0.002{col 58}{space 4} .0924055{col 71}{space 3} .4311161
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2716899{col 30}{space 2} .0487689{col 41}{space 1}    5.57{col 50}{space 3}0.000{col 58}{space 4} .1761045{col 71}{space 3} .3672752
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0222286{col 30}{space 2} .0560658{col 41}{space 1}    0.40{col 50}{space 3}0.692{col 58}{space 4}-.0876584{col 71}{space 3} .1321155
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1316793{col 30}{space 2} .0388549{col 41}{space 1}    3.39{col 50}{space 3}0.001{col 58}{space 4} .0555251{col 71}{space 3} .2078335
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2353328{col 30}{space 2} .0407219{col 41}{space 1}    5.78{col 50}{space 3}0.000{col 58}{space 4} .1555193{col 71}{space 3} .3151463
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1536899{col 30}{space 2} .0340438{col 41}{space 1}   -4.51{col 50}{space 3}0.000{col 58}{space 4}-.2204146{col 71}{space 3}-.0869652
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0039266{col 30}{space 2} .0030548{col 41}{space 1}    1.29{col 50}{space 3}0.199{col 58}{space 4}-.0020607{col 71}{space 3}  .009914
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1350928{col 30}{space 2} .0325499{col 41}{space 1}    4.15{col 50}{space 3}0.000{col 58}{space 4} .0712962{col 71}{space 3} .1988893
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .2803462{col 30}{space 2} .1138401{col 41}{space 1}    2.46{col 50}{space 3}0.014{col 58}{space 4} .0572237{col 71}{space 3} .5034687
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .3996568{col 30}{space 2} .0666283{col 41}{space 1}    6.00{col 50}{space 3}0.000{col 58}{space 4} .2690677{col 71}{space 3} .5302458
{txt}electricity_mean {c |}{col 18}{res}{space 2} .5565236{col 30}{space 2}  .074552{col 41}{space 1}    7.46{col 50}{space 3}0.000{col 58}{space 4} .4104043{col 71}{space 3} .7026428
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.0058507{col 30}{space 2}  .055638{col 41}{space 1}   -0.11{col 50}{space 3}0.916{col 58}{space 4}-.1148992{col 71}{space 3} .1031978
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .2576935{col 30}{space 2} .0574076{col 41}{space 1}    4.49{col 50}{space 3}0.000{col 58}{space 4} .1451768{col 71}{space 3} .3702103
{txt}{space 2}pdd9_mean_town {c |}{col 18}{res}{space 2} .0119884{col 30}{space 2} .0251349{col 41}{space 1}    0.48{col 50}{space 3}0.633{col 58}{space 4}-.0372751{col 71}{space 3} .0612519
{txt}{space 10}year_1 {c |}{col 18}{res}{space 2} .0169396{col 30}{space 2} .0376636{col 41}{space 1}    0.45{col 50}{space 3}0.653{col 58}{space 4}-.0568796{col 71}{space 3} .0907589
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2} .0556129{col 30}{space 2} .0331047{col 41}{space 1}    1.68{col 50}{space 3}0.093{col 58}{space 4}-.0092712{col 71}{space 3}  .120497
{txt}{space 10}year_7 {c |}{col 18}{res}{space 2} .0421274{col 30}{space 2} .0356936{col 41}{space 1}    1.18{col 50}{space 3}0.238{col 58}{space 4}-.0278308{col 71}{space 3} .1120856
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.667922{col 30}{space 2} .1149119{col 41}{space 1}   40.62{col 50}{space 3}0.000{col 58}{space 4} 4.442699{col 71}{space 3} 4.893145
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .76536734
         {txt}sigma_e {c |} {res} 1.2283347
             {txt}rho {c |} {res}  .2796663{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est6
{txt}
{com}. 
. 
. xtreg hdd9  pdd9_town sum_town  $xlist  pdd9_mean_town $year_UGANDA if country==4, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    16,114
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     4,402

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0421                                         {txt}min = {res}         1
{txt}     between = {res}0.2808                                         {txt}avg = {res}       3.7
{txt}     overall = {res}0.1912                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}26{txt})     =  {res}  2522.73
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:4,402} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_town {c |}{col 18}{res}{space 2} .0147563{col 30}{space 2} .0138797{col 41}{space 1}    1.06{col 50}{space 3}0.288{col 58}{space 4}-.0124474{col 71}{space 3} .0419599
{txt}{space 8}sum_town {c |}{col 18}{res}{space 2}-.0170732{col 30}{space 2} .0031232{col 41}{space 1}   -5.47{col 50}{space 3}0.000{col 58}{space 4}-.0231947{col 71}{space 3}-.0109518
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0256898{col 30}{space 2} .0054808{col 41}{space 1}    4.69{col 50}{space 3}0.000{col 58}{space 4} .0149477{col 71}{space 3}  .036432
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0502369{col 30}{space 2}  .060326{col 41}{space 1}    0.83{col 50}{space 3}0.405{col 58}{space 4}-.0679999{col 71}{space 3} .1684738
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0007696{col 30}{space 2} .0010178{col 41}{space 1}   -0.76{col 50}{space 3}0.450{col 58}{space 4}-.0027645{col 71}{space 3} .0012253
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0461251{col 30}{space 2} .0343732{col 41}{space 1}    1.34{col 50}{space 3}0.180{col 58}{space 4} -.021245{col 71}{space 3} .1134953
{txt}{space 7}head_read {c |}{col 18}{res}{space 2}  .322941{col 30}{space 2} .0338457{col 41}{space 1}    9.54{col 50}{space 3}0.000{col 58}{space 4} .2566045{col 71}{space 3} .3892774
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2373777{col 30}{space 2} .0564838{col 41}{space 1}    4.20{col 50}{space 3}0.000{col 58}{space 4} .1266714{col 71}{space 3} .3480839
{txt}{space 11}phone {c |}{col 18}{res}{space 2}  .252401{col 30}{space 2} .0374712{col 41}{space 1}    6.74{col 50}{space 3}0.000{col 58}{space 4} .1789588{col 71}{space 3} .3258432
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .3421277{col 30}{space 2} .0379251{col 41}{space 1}    9.02{col 50}{space 3}0.000{col 58}{space 4} .2677959{col 71}{space 3} .4164594
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0359025{col 30}{space 2} .0305756{col 41}{space 1}    1.17{col 50}{space 3}0.240{col 58}{space 4}-.0240245{col 71}{space 3} .0958295
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}  .202562{col 30}{space 2} .0321543{col 41}{space 1}    6.30{col 50}{space 3}0.000{col 58}{space 4} .1395407{col 71}{space 3} .2655833
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} .0063968{col 30}{space 2} .0250238{col 41}{space 1}    0.26{col 50}{space 3}0.798{col 58}{space 4} -.042649{col 71}{space 3} .0554426
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0015702{col 30}{space 2} .0017172{col 41}{space 1}    0.91{col 50}{space 3}0.360{col 58}{space 4}-.0017953{col 71}{space 3} .0049358
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0503895{col 30}{space 2} .0277635{col 41}{space 1}    1.81{col 50}{space 3}0.070{col 58}{space 4}-.0040259{col 71}{space 3} .1048049
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1402172{col 30}{space 2} .0870363{col 41}{space 1}    1.61{col 50}{space 3}0.107{col 58}{space 4}-.0303709{col 71}{space 3} .3108053
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .3463817{col 30}{space 2} .0621399{col 41}{space 1}    5.57{col 50}{space 3}0.000{col 58}{space 4} .2245897{col 71}{space 3} .4681737
{txt}electricity_mean {c |}{col 18}{res}{space 2} .3752667{col 30}{space 2} .0689561{col 41}{space 1}    5.44{col 50}{space 3}0.000{col 58}{space 4} .2401153{col 71}{space 3} .5104181
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1162884{col 30}{space 2} .0553467{col 41}{space 1}    2.10{col 50}{space 3}0.036{col 58}{space 4} .0078108{col 71}{space 3} .2247659
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .3110433{col 30}{space 2} .0537298{col 41}{space 1}    5.79{col 50}{space 3}0.000{col 58}{space 4} .2057347{col 71}{space 3} .4163518
{txt}{space 2}pdd9_mean_town {c |}{col 18}{res}{space 2} .1898021{col 30}{space 2} .0226143{col 41}{space 1}    8.39{col 50}{space 3}0.000{col 58}{space 4} .1454789{col 71}{space 3} .2341253
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.1348144{col 30}{space 2} .0382795{col 41}{space 1}   -3.52{col 50}{space 3}0.000{col 58}{space 4}-.2098409{col 71}{space 3}-.0597879
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2}-.0482929{col 30}{space 2} .0339705{col 41}{space 1}   -1.42{col 50}{space 3}0.155{col 58}{space 4}-.1148738{col 71}{space 3} .0182881
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .3564511{col 30}{space 2} .0346482{col 41}{space 1}   10.29{col 50}{space 3}0.000{col 58}{space 4} .2885419{col 71}{space 3} .4243604
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2}  .107944{col 30}{space 2} .0344977{col 41}{space 1}    3.13{col 50}{space 3}0.002{col 58}{space 4} .0403297{col 71}{space 3} .1755584
{txt}{space 9}year_10 {c |}{col 18}{res}{space 2} .2933185{col 30}{space 2} .0321388{col 41}{space 1}    9.13{col 50}{space 3}0.000{col 58}{space 4} .2303276{col 71}{space 3} .3563095
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 3.142159{col 30}{space 2} .1307944{col 41}{space 1}   24.02{col 50}{space 3}0.000{col 58}{space 4} 2.885807{col 71}{space 3} 3.398511
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .80192163
         {txt}sigma_e {c |} {res} 1.2678475
             {txt}rho {c |} {res} .28574709{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est7
{txt}
{com}. esttab using  S8.rtf, se replace star(* 0.1 ** 0.05 *** 0.01) cells (b(star fmt(%9.3f)) se (par(( )) fmt(%9.3f)))  stats(N r2_b  r2_w r2_o p, fmt(%4.0f %4.3f %4.3f %6.3f)) keep(pdd9_town    $xlist  pdd9_mean_town sum_town _cons)
{res}{txt}(note: file S8.rtf not found)
(output written to {browse  `"S8.rtf"'})

{com}. 
. 
. ********************************************************************************
. *                                Table S9                                      *
. ********************************************************************************
. eststo clear
{txt}
{com}. xtreg hdd9  pdd9_dist  sum_dist  $xlist pdd9_mean_dist i.country i.year   , cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    65,579
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}    27,229

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0230                                         {txt}min = {res}         1
{txt}     between = {res}0.3626                                         {txt}avg = {res}       2.4
{txt}     overall = {res}0.2804                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}36{txt})     =  {res} 19980.47
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:27,229} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_dist {c |}{col 18}{res}{space 2} .0276536{col 30}{space 2} .0089374{col 41}{space 1}    3.09{col 50}{space 3}0.002{col 58}{space 4} .0101366{col 71}{space 3} .0451706
{txt}{space 8}sum_dist {c |}{col 18}{res}{space 2}-.0012017{col 30}{space 2} .0001735{col 41}{space 1}   -6.92{col 50}{space 3}0.000{col 58}{space 4}-.0015418{col 71}{space 3}-.0008616
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0018877{col 30}{space 2} .0024456{col 41}{space 1}    0.77{col 50}{space 3}0.440{col 58}{space 4}-.0029057{col 71}{space 3} .0066811
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0391904{col 30}{space 2} .0277685{col 41}{space 1}    1.41{col 50}{space 3}0.158{col 58}{space 4}-.0152349{col 71}{space 3} .0936157
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}  .000823{col 30}{space 2} .0004648{col 41}{space 1}    1.77{col 50}{space 3}0.077{col 58}{space 4} -.000088{col 71}{space 3} .0017339
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0489449{col 30}{space 2}  .016976{col 41}{space 1}    2.88{col 50}{space 3}0.004{col 58}{space 4} .0156726{col 71}{space 3} .0822172
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3077784{col 30}{space 2}  .014833{col 41}{space 1}   20.75{col 50}{space 3}0.000{col 58}{space 4} .2787062{col 71}{space 3} .3368506
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1258278{col 30}{space 2} .0294529{col 41}{space 1}    4.27{col 50}{space 3}0.000{col 58}{space 4} .0681013{col 71}{space 3} .1835544
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1764518{col 30}{space 2} .0193197{col 41}{space 1}    9.13{col 50}{space 3}0.000{col 58}{space 4}  .138586{col 71}{space 3} .2143177
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1482962{col 30}{space 2} .0228056{col 41}{space 1}    6.50{col 50}{space 3}0.000{col 58}{space 4}  .103598{col 71}{space 3} .1929943
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1285032{col 30}{space 2} .0199302{col 41}{space 1}    6.45{col 50}{space 3}0.000{col 58}{space 4} .0894408{col 71}{space 3} .1675656
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}  .216961{col 30}{space 2} .0183071{col 41}{space 1}   11.85{col 50}{space 3}0.000{col 58}{space 4} .1810798{col 71}{space 3} .2528422
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0497091{col 30}{space 2} .0142743{col 41}{space 1}   -3.48{col 50}{space 3}0.000{col 58}{space 4}-.0776863{col 71}{space 3}-.0217319
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}   .00056{col 30}{space 2} .0011008{col 41}{space 1}    0.51{col 50}{space 3}0.611{col 58}{space 4}-.0015976{col 71}{space 3} .0027176
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1757759{col 30}{space 2} .0160339{col 41}{space 1}   10.96{col 50}{space 3}0.000{col 58}{space 4} .1443501{col 71}{space 3} .2072017
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0480994{col 30}{space 2} .0396842{col 41}{space 1}    1.21{col 50}{space 3}0.225{col 58}{space 4}-.0296803{col 71}{space 3} .1258791
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .5526723{col 30}{space 2} .0281432{col 41}{space 1}   19.64{col 50}{space 3}0.000{col 58}{space 4} .4975127{col 71}{space 3} .6078319
{txt}electricity_mean {c |}{col 18}{res}{space 2} .6527534{col 30}{space 2} .0307272{col 41}{space 1}   21.24{col 50}{space 3}0.000{col 58}{space 4} .5925291{col 71}{space 3} .7129776
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1543829{col 30}{space 2} .0294354{col 41}{space 1}    5.24{col 50}{space 3}0.000{col 58}{space 4} .0966906{col 71}{space 3} .2120752
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}  .130753{col 30}{space 2} .0256285{col 41}{space 1}    5.10{col 50}{space 3}0.000{col 58}{space 4} .0805221{col 71}{space 3} .1809838
{txt}{space 2}pdd9_mean_dist {c |}{col 18}{res}{space 2} .0690881{col 30}{space 2} .0116031{col 41}{space 1}    5.95{col 50}{space 3}0.000{col 58}{space 4} .0463464{col 71}{space 3} .0918299
{txt}{space 16} {c |}
{space 9}country {c |}
{space 8}Nigeria  {c |}{col 18}{res}{space 2} -.445292{col 30}{space 2}  .033389{col 41}{space 1}  -13.34{col 50}{space 3}0.000{col 58}{space 4}-.5107333{col 71}{space 3}-.3798507
{txt}{space 7}Ethiopia  {c |}{col 18}{res}{space 2}-1.544517{col 30}{space 2} .0374335{col 41}{space 1}  -41.26{col 50}{space 3}0.000{col 58}{space 4}-1.617886{col 71}{space 3}-1.471149
{txt}{space 9}Uganda  {c |}{col 18}{res}{space 2}-.5596247{col 30}{space 2} .0371388{col 41}{space 1}  -15.07{col 50}{space 3}0.000{col 58}{space 4}-.6324154{col 71}{space 3} -.486834
{txt}{space 7}Tanzania  {c |}{col 18}{res}{space 2}-.3500165{col 30}{space 2} .0372157{col 41}{space 1}   -9.41{col 50}{space 3}0.000{col 58}{space 4}-.4229578{col 71}{space 3}-.2770751
{txt}{space 9}Malawi  {c |}{col 18}{res}{space 2} .3556371{col 30}{space 2} .0442729{col 41}{space 1}    8.03{col 50}{space 3}0.000{col 58}{space 4} .2688639{col 71}{space 3} .4424103
{txt}{space 16} {c |}
{space 12}year {c |}
{space 11}2009  {c |}{col 18}{res}{space 2}-.2446711{col 30}{space 2} .0463497{col 41}{space 1}   -5.28{col 50}{space 3}0.000{col 58}{space 4}-.3355148{col 71}{space 3}-.1538274
{txt}{space 11}2010  {c |}{col 18}{res}{space 2} .0149716{col 30}{space 2} .0351828{col 41}{space 1}    0.43{col 50}{space 3}0.670{col 58}{space 4}-.0539853{col 71}{space 3} .0839286
{txt}{space 11}2011  {c |}{col 18}{res}{space 2} .0405378{col 30}{space 2} .0388588{col 41}{space 1}    1.04{col 50}{space 3}0.297{col 58}{space 4} -.035624{col 71}{space 3} .1166996
{txt}{space 11}2012  {c |}{col 18}{res}{space 2} .0198027{col 30}{space 2} .0357446{col 41}{space 1}    0.55{col 50}{space 3}0.580{col 58}{space 4}-.0502555{col 71}{space 3} .0898608
{txt}{space 11}2013  {c |}{col 18}{res}{space 2} .1188008{col 30}{space 2} .0393772{col 41}{space 1}    3.02{col 50}{space 3}0.003{col 58}{space 4} .0416229{col 71}{space 3} .1959787
{txt}{space 11}2014  {c |}{col 18}{res}{space 2}-.0940588{col 30}{space 2} .0394564{col 41}{space 1}   -2.38{col 50}{space 3}0.017{col 58}{space 4} -.171392{col 71}{space 3}-.0167256
{txt}{space 11}2015  {c |}{col 18}{res}{space 2} .1783709{col 30}{space 2} .0381119{col 41}{space 1}    4.68{col 50}{space 3}0.000{col 58}{space 4}  .103673{col 71}{space 3} .2530689
{txt}{space 11}2016  {c |}{col 18}{res}{space 2}-.2198642{col 30}{space 2} .0586947{col 41}{space 1}   -3.75{col 50}{space 3}0.000{col 58}{space 4}-.3349036{col 71}{space 3}-.1048247
{txt}{space 11}2018  {c |}{col 18}{res}{space 2} .4290466{col 30}{space 2} .0403644{col 41}{space 1}   10.63{col 50}{space 3}0.000{col 58}{space 4} .3499339{col 71}{space 3} .5081593
{txt}{space 11}2019  {c |}{col 18}{res}{space 2}-.0101468{col 30}{space 2} .0390861{col 41}{space 1}   -0.26{col 50}{space 3}0.795{col 58}{space 4}-.0867541{col 71}{space 3} .0664606
{txt}{space 16} {c |}
{space 11}_cons {c |}{col 18}{res}{space 2} 4.118053{col 30}{space 2} .0719612{col 41}{space 1}   57.23{col 50}{space 3}0.000{col 58}{space 4} 3.977012{col 71}{space 3} 4.259095
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .80300386
         {txt}sigma_e {c |} {res}  1.237148
             {txt}rho {c |} {res}   .296419{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est1
{txt}
{com}. 
. xtreg hdd9  pdd9_dist  sum_dist  $xlist pdd9_mean_dist $year_ETHIOPIA if country==3, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    11,410
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     4,555

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0208                                         {txt}min = {res}         1
{txt}     between = {res}0.3306                                         {txt}avg = {res}       2.5
{txt}     overall = {res}0.2214                                         {txt}max = {res}         3

                                                {txt}Wald chi2({res}22{txt})     =  {res}  2427.97
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:4,555} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_dist {c |}{col 18}{res}{space 2} .0582772{col 30}{space 2}   .01635{col 41}{space 1}    3.56{col 50}{space 3}0.000{col 58}{space 4} .0262317{col 71}{space 3} .0903227
{txt}{space 8}sum_dist {c |}{col 18}{res}{space 2}-.0050642{col 30}{space 2} .0006027{col 41}{space 1}   -8.40{col 50}{space 3}0.000{col 58}{space 4}-.0062455{col 71}{space 3} -.003883
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0508188{col 30}{space 2} .0070343{col 41}{space 1}    7.22{col 50}{space 3}0.000{col 58}{space 4} .0370318{col 71}{space 3} .0646058
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0501728{col 30}{space 2} .0574816{col 41}{space 1}   -0.87{col 50}{space 3}0.383{col 58}{space 4}-.1628346{col 71}{space 3}  .062489
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0035228{col 30}{space 2} .0009921{col 41}{space 1}   -3.55{col 50}{space 3}0.000{col 58}{space 4}-.0054673{col 71}{space 3}-.0015783
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0568493{col 30}{space 2} .0358722{col 41}{space 1}   -1.58{col 50}{space 3}0.113{col 58}{space 4}-.1271576{col 71}{space 3} .0134589
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3706652{col 30}{space 2} .0314203{col 41}{space 1}   11.80{col 50}{space 3}0.000{col 58}{space 4} .3090826{col 71}{space 3} .4322478
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}-.2144557{col 30}{space 2} .1576262{col 41}{space 1}   -1.36{col 50}{space 3}0.174{col 58}{space 4}-.5233974{col 71}{space 3}  .094486
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1805397{col 30}{space 2} .0377566{col 41}{space 1}    4.78{col 50}{space 3}0.000{col 58}{space 4}  .106538{col 71}{space 3} .2545413
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1631594{col 30}{space 2} .0460696{col 41}{space 1}    3.54{col 50}{space 3}0.000{col 58}{space 4} .0728647{col 71}{space 3} .2534541
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0772026{col 30}{space 2} .0632147{col 41}{space 1}    1.22{col 50}{space 3}0.222{col 58}{space 4}-.0466959{col 71}{space 3} .2011012
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2202839{col 30}{space 2} .0499724{col 41}{space 1}    4.41{col 50}{space 3}0.000{col 58}{space 4} .1223398{col 71}{space 3} .3182281
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1216917{col 30}{space 2} .0295897{col 41}{space 1}   -4.11{col 50}{space 3}0.000{col 58}{space 4}-.1796864{col 71}{space 3} -.063697
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0130256{col 30}{space 2} .0036071{col 41}{space 1}    3.61{col 50}{space 3}0.000{col 58}{space 4} .0059558{col 71}{space 3} .0200954
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .2958851{col 30}{space 2} .0308028{col 41}{space 1}    9.61{col 50}{space 3}0.000{col 58}{space 4} .2355127{col 71}{space 3} .3562575
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .9844681{col 30}{space 2} .2615728{col 41}{space 1}    3.76{col 50}{space 3}0.000{col 58}{space 4} .4717949{col 71}{space 3} 1.497141
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .4577851{col 30}{space 2} .0569903{col 41}{space 1}    8.03{col 50}{space 3}0.000{col 58}{space 4} .3460861{col 71}{space 3} .5694841
{txt}electricity_mean {c |}{col 18}{res}{space 2} .4724606{col 30}{space 2} .0667995{col 41}{space 1}    7.07{col 50}{space 3}0.000{col 58}{space 4}  .341536{col 71}{space 3} .6033851
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .4264689{col 30}{space 2} .0972725{col 41}{space 1}    4.38{col 50}{space 3}0.000{col 58}{space 4} .2358184{col 71}{space 3} .6171194
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .0952955{col 30}{space 2} .0635327{col 41}{space 1}    1.50{col 50}{space 3}0.134{col 58}{space 4}-.0292264{col 71}{space 3} .2198173
{txt}{space 2}pdd9_mean_dist {c |}{col 18}{res}{space 2} .0205645{col 30}{space 2} .0199462{col 41}{space 1}    1.03{col 50}{space 3}0.303{col 58}{space 4}-.0185292{col 71}{space 3} .0596583
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}-.1411127{col 30}{space 2} .0221299{col 41}{space 1}   -6.38{col 50}{space 3}0.000{col 58}{space 4}-.1844866{col 71}{space 3}-.0977388
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 2.954891{col 30}{space 2} .0957704{col 41}{space 1}   30.85{col 50}{space 3}0.000{col 58}{space 4} 2.767184{col 71}{space 3} 3.142597
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .73382677
         {txt}sigma_e {c |} {res} 1.0775436
             {txt}rho {c |} {res}  .3168399{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est2
{txt}
{com}. 
. xtreg hdd9  pdd9_dist  sum_dist  $xlist pdd9_mean_dist $year_MALAWI  if country==6, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     4,626
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     1,571

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0217                                         {txt}min = {res}         1
{txt}     between = {res}0.3946                                         {txt}avg = {res}       2.9
{txt}     overall = {res}0.2768                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}23{txt})     =  {res}  1533.84
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:1,571} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_dist {c |}{col 18}{res}{space 2}-.0427328{col 30}{space 2} .0416063{col 41}{space 1}   -1.03{col 50}{space 3}0.304{col 58}{space 4}-.1242796{col 71}{space 3} .0388139
{txt}{space 8}sum_dist {c |}{col 18}{res}{space 2}-.0039425{col 30}{space 2} .0009734{col 41}{space 1}   -4.05{col 50}{space 3}0.000{col 58}{space 4}-.0058503{col 71}{space 3}-.0020346
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0021482{col 30}{space 2}  .011228{col 41}{space 1}   -0.19{col 50}{space 3}0.848{col 58}{space 4}-.0241547{col 71}{space 3} .0198583
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} -.269356{col 30}{space 2} .1030895{col 41}{space 1}   -2.61{col 50}{space 3}0.009{col 58}{space 4}-.4714077{col 71}{space 3}-.0673043
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0017041{col 30}{space 2} .0017104{col 41}{space 1}   -1.00{col 50}{space 3}0.319{col 58}{space 4}-.0050563{col 71}{space 3} .0016482
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.1063593{col 30}{space 2} .0598905{col 41}{space 1}   -1.78{col 50}{space 3}0.076{col 58}{space 4}-.2237426{col 71}{space 3}  .011024
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2998328{col 30}{space 2} .0585464{col 41}{space 1}    5.12{col 50}{space 3}0.000{col 58}{space 4} .1850841{col 71}{space 3} .4145816
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2643125{col 30}{space 2} .1903361{col 41}{space 1}    1.39{col 50}{space 3}0.165{col 58}{space 4}-.1087393{col 71}{space 3} .6373644
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1124799{col 30}{space 2} .0695981{col 41}{space 1}    1.62{col 50}{space 3}0.106{col 58}{space 4}-.0239299{col 71}{space 3} .2488897
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .2210991{col 30}{space 2} .1397919{col 41}{space 1}    1.58{col 50}{space 3}0.114{col 58}{space 4} -.052888{col 71}{space 3} .4950861
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1382601{col 30}{space 2} .0811021{col 41}{space 1}    1.70{col 50}{space 3}0.088{col 58}{space 4}-.0206971{col 71}{space 3} .2972173
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2579415{col 30}{space 2} .0561605{col 41}{space 1}    4.59{col 50}{space 3}0.000{col 58}{space 4}  .147869{col 71}{space 3} .3680141
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1630508{col 30}{space 2} .0432669{col 41}{space 1}   -3.77{col 50}{space 3}0.000{col 58}{space 4}-.2478523{col 71}{space 3}-.0782492
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0918483{col 30}{space 2} .0337144{col 41}{space 1}    2.72{col 50}{space 3}0.006{col 58}{space 4} .0257693{col 71}{space 3} .1579274
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0908392{col 30}{space 2} .0620618{col 41}{space 1}    1.46{col 50}{space 3}0.143{col 58}{space 4}-.0307997{col 71}{space 3} .2124781
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0041397{col 30}{space 2} .3139129{col 41}{space 1}    0.01{col 50}{space 3}0.989{col 58}{space 4}-.6111183{col 71}{space 3} .6193976
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .7179215{col 30}{space 2} .1081372{col 41}{space 1}    6.64{col 50}{space 3}0.000{col 58}{space 4} .5059765{col 71}{space 3} .9298664
{txt}electricity_mean {c |}{col 18}{res}{space 2} .8662439{col 30}{space 2} .1742381{col 41}{space 1}    4.97{col 50}{space 3}0.000{col 58}{space 4} .5247434{col 71}{space 3} 1.207744
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .3508242{col 30}{space 2} .1140328{col 41}{space 1}    3.08{col 50}{space 3}0.002{col 58}{space 4}  .127324{col 71}{space 3} .5743244
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .2763338{col 30}{space 2} .0997502{col 41}{space 1}    2.77{col 50}{space 3}0.006{col 58}{space 4}  .080827{col 71}{space 3} .4718406
{txt}{space 2}pdd9_mean_dist {c |}{col 18}{res}{space 2}-.0187495{col 30}{space 2} .0656245{col 41}{space 1}   -0.29{col 50}{space 3}0.775{col 58}{space 4}-.1473711{col 71}{space 3} .1098721
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2} .2386601{col 30}{space 2} .0566011{col 41}{space 1}    4.22{col 50}{space 3}0.000{col 58}{space 4} .1277241{col 71}{space 3} .3495962
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .1035806{col 30}{space 2} .0498277{col 41}{space 1}    2.08{col 50}{space 3}0.038{col 58}{space 4} .0059202{col 71}{space 3}  .201241
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 5.714456{col 30}{space 2} .3751176{col 41}{space 1}   15.23{col 50}{space 3}0.000{col 58}{space 4} 4.979239{col 71}{space 3} 6.449673
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res}  .6940838
         {txt}sigma_e {c |} {res} 1.2904179
             {txt}rho {c |} {res}  .2243912{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est3
{txt}
{com}. 
. xtreg hdd9 pdd9_dist  sum_dist  $xlist pdd9_mean_dist $year_NIGER if country==1, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     6,536
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     3,837

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0217                                         {txt}min = {res}         1
{txt}     between = {res}0.2269                                         {txt}avg = {res}       1.7
{txt}     overall = {res}0.1715                                         {txt}max = {res}         2

                                                {txt}Wald chi2({res}22{txt})     =  {res}  1329.24
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,837} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_dist {c |}{col 18}{res}{space 2} .0280138{col 30}{space 2} .0443403{col 41}{space 1}    0.63{col 50}{space 3}0.528{col 58}{space 4}-.0588916{col 71}{space 3} .1149192
{txt}{space 8}sum_dist {c |}{col 18}{res}{space 2} .0004621{col 30}{space 2} .0002761{col 41}{space 1}    1.67{col 50}{space 3}0.094{col 58}{space 4}-.0000791{col 71}{space 3} .0010033
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0138417{col 30}{space 2} .0063937{col 41}{space 1}    2.16{col 50}{space 3}0.030{col 58}{space 4} .0013102{col 71}{space 3} .0263733
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.1308327{col 30}{space 2} .0997915{col 41}{space 1}   -1.31{col 50}{space 3}0.190{col 58}{space 4}-.3264205{col 71}{space 3}  .064755
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0029147{col 30}{space 2} .0014241{col 41}{space 1}    2.05{col 50}{space 3}0.041{col 58}{space 4} .0001235{col 71}{space 3} .0057059
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0796704{col 30}{space 2} .0590139{col 41}{space 1}    1.35{col 50}{space 3}0.177{col 58}{space 4}-.0359948{col 71}{space 3} .1953355
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3602885{col 30}{space 2} .0461414{col 41}{space 1}    7.81{col 50}{space 3}0.000{col 58}{space 4}  .269853{col 71}{space 3}  .450724
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .3392855{col 30}{space 2} .1115464{col 41}{space 1}    3.04{col 50}{space 3}0.002{col 58}{space 4} .1206585{col 71}{space 3} .5579125
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1178639{col 30}{space 2} .0789948{col 41}{space 1}    1.49{col 50}{space 3}0.136{col 58}{space 4}-.0369631{col 71}{space 3} .2726908
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .2600981{col 30}{space 2} .1250755{col 41}{space 1}    2.08{col 50}{space 3}0.038{col 58}{space 4} .0149546{col 71}{space 3} .5052415
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2209914{col 30}{space 2} .0910413{col 41}{space 1}    2.43{col 50}{space 3}0.015{col 58}{space 4} .0425537{col 71}{space 3}  .399429
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}-.1571584{col 30}{space 2}  .070024{col 41}{space 1}   -2.24{col 50}{space 3}0.025{col 58}{space 4}-.2944028{col 71}{space 3} -.019914
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1152895{col 30}{space 2} .0453972{col 41}{space 1}   -2.54{col 50}{space 3}0.011{col 58}{space 4}-.2042664{col 71}{space 3}-.0263126
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0008811{col 30}{space 2} .0015428{col 41}{space 1}   -0.57{col 50}{space 3}0.568{col 58}{space 4}-.0039049{col 71}{space 3} .0021426
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .2143656{col 30}{space 2} .2173695{col 41}{space 1}    0.99{col 50}{space 3}0.324{col 58}{space 4}-.2116709{col 71}{space 3}  .640402
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}-.0077269{col 30}{space 2} .1340696{col 41}{space 1}   -0.06{col 50}{space 3}0.954{col 58}{space 4}-.2704986{col 71}{space 3} .2550448
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .3010089{col 30}{space 2} .0959762{col 41}{space 1}    3.14{col 50}{space 3}0.002{col 58}{space 4}  .112899{col 71}{space 3} .4891188
{txt}electricity_mean {c |}{col 18}{res}{space 2} .4569079{col 30}{space 2} .1410132{col 41}{space 1}    3.24{col 50}{space 3}0.001{col 58}{space 4} .1805271{col 71}{space 3} .7332888
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1801128{col 30}{space 2} .1114804{col 41}{space 1}    1.62{col 50}{space 3}0.106{col 58}{space 4}-.0383848{col 71}{space 3} .3986105
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .4085646{col 30}{space 2} .0855039{col 41}{space 1}    4.78{col 50}{space 3}0.000{col 58}{space 4} .2409801{col 71}{space 3} .5761491
{txt}{space 2}pdd9_mean_dist {c |}{col 18}{res}{space 2} .0603026{col 30}{space 2} .0530092{col 41}{space 1}    1.14{col 50}{space 3}0.255{col 58}{space 4}-.0435936{col 71}{space 3} .1641987
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2} .2382424{col 30}{space 2} .0389254{col 41}{space 1}    6.12{col 50}{space 3}0.000{col 58}{space 4} .1619499{col 71}{space 3} .3145348
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 3.915618{col 30}{space 2} .1944536{col 41}{space 1}   20.14{col 50}{space 3}0.000{col 58}{space 4} 3.534496{col 71}{space 3}  4.29674
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .54604504
         {txt}sigma_e {c |} {res} 1.4004196
             {txt}rho {c |} {res} .13197002{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est4
{txt}
{com}. 
. 
. xtreg hdd9  pdd9_dist  sum_dist  $xlist pdd9_mean_dist $year_NIGERIA if country==2, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    15,063
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     7,154

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0387                                         {txt}min = {res}         1
{txt}     between = {res}0.3033                                         {txt}avg = {res}       2.1
{txt}     overall = {res}0.2575                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}24{txt})     =  {res}  4029.91
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:7,154} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_dist {c |}{col 18}{res}{space 2} .1108346{col 30}{space 2} .0200641{col 41}{space 1}    5.52{col 50}{space 3}0.000{col 58}{space 4} .0715096{col 71}{space 3} .1501596
{txt}{space 8}sum_dist {c |}{col 18}{res}{space 2}-.0035127{col 30}{space 2} .0003529{col 41}{space 1}   -9.95{col 50}{space 3}0.000{col 58}{space 4}-.0042044{col 71}{space 3} -.002821
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0215824{col 30}{space 2} .0046646{col 41}{space 1}   -4.63{col 50}{space 3}0.000{col 58}{space 4} -.030725{col 71}{space 3}-.0124399
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .1369363{col 30}{space 2} .0539404{col 41}{space 1}    2.54{col 50}{space 3}0.011{col 58}{space 4} .0312151{col 71}{space 3} .2426576
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0049665{col 30}{space 2} .0009687{col 41}{space 1}    5.13{col 50}{space 3}0.000{col 58}{space 4} .0030678{col 71}{space 3} .0068651
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .3057108{col 30}{space 2} .0392666{col 41}{space 1}    7.79{col 50}{space 3}0.000{col 58}{space 4} .2287497{col 71}{space 3} .3826719
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2000568{col 30}{space 2} .0286167{col 41}{space 1}    6.99{col 50}{space 3}0.000{col 58}{space 4}  .143969{col 71}{space 3} .2561445
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0152803{col 30}{space 2} .0418486{col 41}{space 1}    0.37{col 50}{space 3}0.715{col 58}{space 4}-.0667415{col 71}{space 3}  .097302
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1623581{col 30}{space 2} .0405444{col 41}{space 1}    4.00{col 50}{space 3}0.000{col 58}{space 4} .0828926{col 71}{space 3} .2418236
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0839806{col 30}{space 2}   .04927{col 41}{space 1}    1.70{col 50}{space 3}0.088{col 58}{space 4}-.0125867{col 71}{space 3}  .180548
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}  .244721{col 30}{space 2} .0572544{col 41}{space 1}    4.27{col 50}{space 3}0.000{col 58}{space 4} .1325044{col 71}{space 3} .3569376
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .3022339{col 30}{space 2}  .043348{col 41}{space 1}    6.97{col 50}{space 3}0.000{col 58}{space 4} .2172733{col 71}{space 3} .3871944
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} .0303851{col 30}{space 2} .0468014{col 41}{space 1}    0.65{col 50}{space 3}0.516{col 58}{space 4}-.0613439{col 71}{space 3} .1221142
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} -.005451{col 30}{space 2} .0059804{col 41}{space 1}   -0.91{col 50}{space 3}0.362{col 58}{space 4}-.0171723{col 71}{space 3} .0062703
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .2940182{col 30}{space 2} .0603557{col 41}{space 1}    4.87{col 50}{space 3}0.000{col 58}{space 4} .1757232{col 71}{space 3} .4123133
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0945555{col 30}{space 2} .0565099{col 41}{space 1}    1.67{col 50}{space 3}0.094{col 58}{space 4}-.0162019{col 71}{space 3} .2053128
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .7441403{col 30}{space 2} .0601907{col 41}{space 1}   12.36{col 50}{space 3}0.000{col 58}{space 4} .6261686{col 71}{space 3}  .862112
{txt}electricity_mean {c |}{col 18}{res}{space 2} .8025566{col 30}{space 2} .0612616{col 41}{space 1}   13.10{col 50}{space 3}0.000{col 58}{space 4} .6824861{col 71}{space 3} .9226272
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1061265{col 30}{space 2} .0742279{col 41}{space 1}    1.43{col 50}{space 3}0.153{col 58}{space 4}-.0393574{col 71}{space 3} .2516105
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.0878694{col 30}{space 2}  .055458{col 41}{space 1}   -1.58{col 50}{space 3}0.113{col 58}{space 4}-.1965651{col 71}{space 3} .0208264
{txt}{space 2}pdd9_mean_dist {c |}{col 18}{res}{space 2}-.0493682{col 30}{space 2} .0272854{col 41}{space 1}   -1.81{col 50}{space 3}0.070{col 58}{space 4}-.1028467{col 71}{space 3} .0041102
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.5865297{col 30}{space 2} .0357736{col 41}{space 1}  -16.40{col 50}{space 3}0.000{col 58}{space 4}-.6566446{col 71}{space 3}-.5164147
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2}-.5243649{col 30}{space 2} .0364531{col 41}{space 1}  -14.38{col 50}{space 3}0.000{col 58}{space 4}-.5958116{col 71}{space 3}-.4529181
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2}-.3804863{col 30}{space 2} .0368997{col 41}{space 1}  -10.31{col 50}{space 3}0.000{col 58}{space 4}-.4528084{col 71}{space 3}-.3081643
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.518663{col 30}{space 2} .1694326{col 41}{space 1}   26.67{col 50}{space 3}0.000{col 58}{space 4} 4.186581{col 71}{space 3} 4.850745
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .86132363
         {txt}sigma_e {c |} {res} 1.2207038
             {txt}rho {c |} {res} .33238337{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est5
{txt}
{com}. 
. 
. xtreg hdd9  pdd9_dist  sum_dist  $xlist pdd9_mean_dist $year_TANZANIA if country==5, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    11,830
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     5,710

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0139                                         {txt}min = {res}         1
{txt}     between = {res}0.2238                                         {txt}avg = {res}       2.1
{txt}     overall = {res}0.1683                                         {txt}max = {res}         5

                                                {txt}Wald chi2({res}24{txt})     =  {res}  1841.23
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:5,710} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_dist {c |}{col 18}{res}{space 2}-.0348218{col 30}{space 2} .0263021{col 41}{space 1}   -1.32{col 50}{space 3}0.186{col 58}{space 4}-.0863731{col 71}{space 3} .0167294
{txt}{space 8}sum_dist {c |}{col 18}{res}{space 2} .0010149{col 30}{space 2} .0010743{col 41}{space 1}    0.94{col 50}{space 3}0.345{col 58}{space 4}-.0010907{col 71}{space 3} .0031204
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0013754{col 30}{space 2}  .005311{col 41}{space 1}   -0.26{col 50}{space 3}0.796{col 58}{space 4}-.0117847{col 71}{space 3}  .009034
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0512644{col 30}{space 2} .0656109{col 41}{space 1}    0.78{col 50}{space 3}0.435{col 58}{space 4}-.0773306{col 71}{space 3} .1798594
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0011826{col 30}{space 2} .0010481{col 41}{space 1}   -1.13{col 50}{space 3}0.259{col 58}{space 4}-.0032368{col 71}{space 3} .0008716
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0261261{col 30}{space 2} .0372185{col 41}{space 1}    0.70{col 50}{space 3}0.483{col 58}{space 4}-.0468209{col 71}{space 3} .0990731
{txt}{space 7}head_read {c |}{col 18}{res}{space 2}  .278076{col 30}{space 2}  .035345{col 41}{space 1}    7.87{col 50}{space 3}0.000{col 58}{space 4}  .208801{col 71}{space 3} .3473509
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2557324{col 30}{space 2} .0864844{col 41}{space 1}    2.96{col 50}{space 3}0.003{col 58}{space 4} .0862262{col 71}{space 3} .4252386
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2726461{col 30}{space 2} .0487599{col 41}{space 1}    5.59{col 50}{space 3}0.000{col 58}{space 4} .1770784{col 71}{space 3} .3682137
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0325489{col 30}{space 2} .0560783{col 41}{space 1}    0.58{col 50}{space 3}0.562{col 58}{space 4}-.0773625{col 71}{space 3} .1424603
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1300051{col 30}{space 2} .0388652{col 41}{space 1}    3.35{col 50}{space 3}0.001{col 58}{space 4} .0538307{col 71}{space 3} .2061795
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2345506{col 30}{space 2} .0406673{col 41}{space 1}    5.77{col 50}{space 3}0.000{col 58}{space 4} .1548441{col 71}{space 3}  .314257
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1548711{col 30}{space 2} .0340538{col 41}{space 1}   -4.55{col 50}{space 3}0.000{col 58}{space 4}-.2216154{col 71}{space 3}-.0881268
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0029692{col 30}{space 2} .0030479{col 41}{space 1}    0.97{col 50}{space 3}0.330{col 58}{space 4}-.0030045{col 71}{space 3} .0089429
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1213342{col 30}{space 2} .0322537{col 41}{space 1}    3.76{col 50}{space 3}0.000{col 58}{space 4} .0581182{col 71}{space 3} .1845502
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .2791305{col 30}{space 2} .1139429{col 41}{space 1}    2.45{col 50}{space 3}0.014{col 58}{space 4} .0558065{col 71}{space 3} .5024545
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .4097653{col 30}{space 2} .0664276{col 41}{space 1}    6.17{col 50}{space 3}0.000{col 58}{space 4} .2795696{col 71}{space 3}  .539961
{txt}electricity_mean {c |}{col 18}{res}{space 2} .5736707{col 30}{space 2} .0739148{col 41}{space 1}    7.76{col 50}{space 3}0.000{col 58}{space 4} .4288004{col 71}{space 3} .7185411
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.0057067{col 30}{space 2} .0555978{col 41}{space 1}   -0.10{col 50}{space 3}0.918{col 58}{space 4}-.1146763{col 71}{space 3}  .103263
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .2516718{col 30}{space 2} .0574227{col 41}{space 1}    4.38{col 50}{space 3}0.000{col 58}{space 4} .1391254{col 71}{space 3} .3642183
{txt}{space 2}pdd9_mean_dist {c |}{col 18}{res}{space 2} .0873343{col 30}{space 2} .0337592{col 41}{space 1}    2.59{col 50}{space 3}0.010{col 58}{space 4} .0211676{col 71}{space 3} .1535011
{txt}{space 10}year_1 {c |}{col 18}{res}{space 2} .0302565{col 30}{space 2} .0379631{col 41}{space 1}    0.80{col 50}{space 3}0.425{col 58}{space 4}-.0441498{col 71}{space 3} .1046627
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2} .0312097{col 30}{space 2} .0339707{col 41}{space 1}    0.92{col 50}{space 3}0.358{col 58}{space 4}-.0353717{col 71}{space 3}  .097791
{txt}{space 10}year_7 {c |}{col 18}{res}{space 2} .0551242{col 30}{space 2} .0358309{col 41}{space 1}    1.54{col 50}{space 3}0.124{col 58}{space 4}-.0151031{col 71}{space 3} .1253515
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 4.214838{col 30}{space 2} .1676226{col 41}{space 1}   25.14{col 50}{space 3}0.000{col 58}{space 4} 3.886304{col 71}{space 3} 4.543372
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .76782572
         {txt}sigma_e {c |} {res} 1.2278813
             {txt}rho {c |} {res} .28110939{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est6
{txt}
{com}. 
. 
. xtreg hdd9  pdd9_dist  sum_dist  $xlist pdd9_mean_dist $year_UGANDA if country==4, cluster(HHID_panel) 
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}    16,114
{txt}Group variable: {res}HHID_panel                      {txt}Number of groups  = {res}     4,402

{txt}R-sq:                                           Obs per group:
     within  = {res}0.0424                                         {txt}min = {res}         1
{txt}     between = {res}0.2765                                         {txt}avg = {res}       3.7
{txt}     overall = {res}0.1892                                         {txt}max = {res}         7

                                                {txt}Wald chi2({res}26{txt})     =  {res}  2415.31
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:4,402} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_dist {c |}{col 18}{res}{space 2} .0149778{col 30}{space 2} .0171948{col 41}{space 1}    0.87{col 50}{space 3}0.384{col 58}{space 4}-.0187234{col 71}{space 3}  .048679
{txt}{space 8}sum_dist {c |}{col 18}{res}{space 2} .0001254{col 30}{space 2} .0009542{col 41}{space 1}    0.13{col 50}{space 3}0.895{col 58}{space 4}-.0017447{col 71}{space 3} .0019956
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0300247{col 30}{space 2} .0054889{col 41}{space 1}    5.47{col 50}{space 3}0.000{col 58}{space 4} .0192667{col 71}{space 3} .0407828
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0569559{col 30}{space 2}  .060222{col 41}{space 1}    0.95{col 50}{space 3}0.344{col 58}{space 4} -.061077{col 71}{space 3} .1749888
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0007224{col 30}{space 2}  .001022{col 41}{space 1}   -0.71{col 50}{space 3}0.480{col 58}{space 4}-.0027255{col 71}{space 3} .0012808
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0350735{col 30}{space 2}  .034418{col 41}{space 1}    1.02{col 50}{space 3}0.308{col 58}{space 4}-.0323845{col 71}{space 3} .1025315
{txt}{space 7}head_read {c |}{col 18}{res}{space 2}  .317831{col 30}{space 2} .0338328{col 41}{space 1}    9.39{col 50}{space 3}0.000{col 58}{space 4} .2515199{col 71}{space 3} .3841422
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2364591{col 30}{space 2} .0563699{col 41}{space 1}    4.19{col 50}{space 3}0.000{col 58}{space 4} .1259761{col 71}{space 3} .3469421
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2487883{col 30}{space 2} .0374789{col 41}{space 1}    6.64{col 50}{space 3}0.000{col 58}{space 4}  .175331{col 71}{space 3} .3222456
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .3407008{col 30}{space 2} .0379529{col 41}{space 1}    8.98{col 50}{space 3}0.000{col 58}{space 4} .2663144{col 71}{space 3} .4150871
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0359354{col 30}{space 2} .0305883{col 41}{space 1}    1.17{col 50}{space 3}0.240{col 58}{space 4}-.0240166{col 71}{space 3} .0958873
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2020548{col 30}{space 2} .0321562{col 41}{space 1}    6.28{col 50}{space 3}0.000{col 58}{space 4} .1390299{col 71}{space 3} .2650797
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} .0244943{col 30}{space 2} .0250646{col 41}{space 1}    0.98{col 50}{space 3}0.328{col 58}{space 4}-.0246314{col 71}{space 3}   .07362
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0024588{col 30}{space 2} .0018195{col 41}{space 1}    1.35{col 50}{space 3}0.177{col 58}{space 4}-.0011074{col 71}{space 3} .0060249
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0654561{col 30}{space 2} .0277929{col 41}{space 1}    2.36{col 50}{space 3}0.019{col 58}{space 4}  .010983{col 71}{space 3} .1199292
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1259603{col 30}{space 2} .0870294{col 41}{space 1}    1.45{col 50}{space 3}0.148{col 58}{space 4}-.0446141{col 71}{space 3} .2965348
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .3358245{col 30}{space 2} .0625471{col 41}{space 1}    5.37{col 50}{space 3}0.000{col 58}{space 4} .2132344{col 71}{space 3} .4584145
{txt}electricity_mean {c |}{col 18}{res}{space 2} .3145981{col 30}{space 2} .0690216{col 41}{space 1}    4.56{col 50}{space 3}0.000{col 58}{space 4} .1793183{col 71}{space 3} .4498779
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .0727587{col 30}{space 2} .0555769{col 41}{space 1}    1.31{col 50}{space 3}0.190{col 58}{space 4}-.0361699{col 71}{space 3} .1816874
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .2914896{col 30}{space 2} .0536726{col 41}{space 1}    5.43{col 50}{space 3}0.000{col 58}{space 4} .1862934{col 71}{space 3} .3966859
{txt}{space 2}pdd9_mean_dist {c |}{col 18}{res}{space 2} .2106741{col 30}{space 2}  .029668{col 41}{space 1}    7.10{col 50}{space 3}0.000{col 58}{space 4} .1525258{col 71}{space 3} .2688223
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.1398641{col 30}{space 2} .0384604{col 41}{space 1}   -3.64{col 50}{space 3}0.000{col 58}{space 4}-.2152451{col 71}{space 3}-.0644831
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2}-.0553303{col 30}{space 2} .0343198{col 41}{space 1}   -1.61{col 50}{space 3}0.107{col 58}{space 4}-.1225958{col 71}{space 3} .0119353
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .3402228{col 30}{space 2} .0346634{col 41}{space 1}    9.82{col 50}{space 3}0.000{col 58}{space 4} .2722837{col 71}{space 3} .4081618
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2} .0938754{col 30}{space 2} .0345239{col 41}{space 1}    2.72{col 50}{space 3}0.007{col 58}{space 4} .0262097{col 71}{space 3}  .161541
{txt}{space 9}year_10 {c |}{col 18}{res}{space 2} .2852875{col 30}{space 2} .0323152{col 41}{space 1}    8.83{col 50}{space 3}0.000{col 58}{space 4}  .221951{col 71}{space 3} .3486241
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 2.615979{col 30}{space 2} .1818335{col 41}{space 1}   14.39{col 50}{space 3}0.000{col 58}{space 4} 2.259592{col 71}{space 3} 2.972366
{txt}{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
         sigma_u {c |} {res} .80655393
         {txt}sigma_e {c |} {res} 1.2676197
             {txt}rho {c |} {res} .28817773{txt}   (fraction of variance due to u_i)
{hline 17}{c BT}{hline 64}

{com}. eststo est7
{txt}
{com}. esttab using  S9.rtf, se replace star(* 0.1 ** 0.05 *** 0.01) cells (b(star fmt(%9.3f)) se (par(( )) fmt(%9.3f)))  stats(N r2_b  r2_w r2_o p, fmt(%4.0f %4.3f %4.3f %6.3f)) keep(pdd9_dist    $xlist  pdd9_mean_dist sum_dist _cons)
{res}{txt}(note: file S9.rtf not found)
(output written to {browse  `"S9.rtf"'})

{com}. restore
{txt}
{com}. 
. 
. ********************************************************************************
. *                                Table S19                                     *
. ********************************************************************************
. preserve
{txt}
{com}. mat Y = J(100,5,.)
{txt}
{com}. local tt "   hhsize dependent_share head_age female_head head_read  motobike phone  electricity wagejob enterprise weather_shock  plot_area other_crop dist_popcenter"
{txt}
{com}. 
. local g 1
{txt}
{com}. foreach var of varlist `tt'  {c -(}
{txt}  2{com}. ttest `var'=0
{txt}  3{com}. mat Y[`g',1] = r(mu_1)
{txt}  4{com}. mat Y[`g',2] = r(sd_1)
{txt}  5{com}. local g=`g'+1
{txt}  6{com}. 
. {c )-}

{txt}One-sample t test
{hline 9}{c TT}{hline 68}
Variable{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. Err.{col 47}Std. Dev.{col 59}[95% Conf. Interval]
{hline 9}{c +}{hline 68}
  hhsize {c |}{res}{col 12} 89,742{col 22} 5.364044{col 34} .0099148{col 46} 2.970184{col 58} 5.344611{col 70} 5.383477
{txt}{hline 9}{c BT}{hline 68}
    mean = mean({res}hhsize{txt})                                           t = {res}541.0118
{txt}Ho: mean = {res}0                                     {txt}degrees of freedom = {res}   89741

    {txt}Ha: mean < {res}0                 {txt}Ha: mean != {res}0                 {txt}Ha: mean > {res}0
 {txt}Pr(T < t) = {res}1.0000         {txt}Pr(|T| > |t|) = {res}0.0000          {txt}Pr(T > t) = {res}0.0000

{txt}One-sample t test
{hline 9}{c TT}{hline 68}
Variable{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. Err.{col 47}Std. Dev.{col 59}[95% Conf. Interval]
{hline 9}{c +}{hline 68}
depend~e {c |}{res}{col 12} 89,742{col 22} .4483005{col 34} .0008305{col 46}  .248803{col 58} .4466727{col 70} .4499284
{txt}{hline 9}{c BT}{hline 68}
    mean = mean({res}dependent_share{txt})                                  t = {res}539.7735
{txt}Ho: mean = {res}0                                     {txt}degrees of freedom = {res}   89741

    {txt}Ha: mean < {res}0                 {txt}Ha: mean != {res}0                 {txt}Ha: mean > {res}0
 {txt}Pr(T < t) = {res}1.0000         {txt}Pr(|T| > |t|) = {res}0.0000          {txt}Pr(T > t) = {res}0.0000

{txt}One-sample t test
{hline 9}{c TT}{hline 68}
Variable{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. Err.{col 47}Std. Dev.{col 59}[95% Conf. Interval]
{hline 9}{c +}{hline 68}
head_age {c |}{res}{col 12} 89,742{col 22} 46.53567{col 34} .0520167{col 46} 15.58264{col 58} 46.43372{col 70} 46.63762
{txt}{hline 9}{c BT}{hline 68}
    mean = mean({res}head_age{txt})                                         t = {res}894.6289
{txt}Ho: mean = {res}0                                     {txt}degrees of freedom = {res}   89741

    {txt}Ha: mean < {res}0                 {txt}Ha: mean != {res}0                 {txt}Ha: mean > {res}0
 {txt}Pr(T < t) = {res}1.0000         {txt}Pr(|T| > |t|) = {res}0.0000          {txt}Pr(T > t) = {res}0.0000

{txt}One-sample t test
{hline 9}{c TT}{hline 68}
Variable{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. Err.{col 47}Std. Dev.{col 59}[95% Conf. Interval]
{hline 9}{c +}{hline 68}
female~d {c |}{res}{col 12} 89,742{col 22} .2514653{col 34} .0014483{col 46} .4338578{col 58} .2486267{col 70} .2543039
{txt}{hline 9}{c BT}{hline 68}
    mean = mean({res}female_head{txt})                                      t = {res}173.6315
{txt}Ho: mean = {res}0                                     {txt}degrees of freedom = {res}   89741

    {txt}Ha: mean < {res}0                 {txt}Ha: mean != {res}0                 {txt}Ha: mean > {res}0
 {txt}Pr(T < t) = {res}1.0000         {txt}Pr(|T| > |t|) = {res}0.0000          {txt}Pr(T > t) = {res}0.0000

{txt}One-sample t test
{hline 9}{c TT}{hline 68}
Variable{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. Err.{col 47}Std. Dev.{col 59}[95% Conf. Interval]
{hline 9}{c +}{hline 68}
head_r~d {c |}{res}{col 12} 89,742{col 22} .6483921{col 34} .0015939{col 46}  .477475{col 58} .6452681{col 70}  .651516
{txt}{hline 9}{c BT}{hline 68}
    mean = mean({res}head_read{txt})                                        t = {res}406.8038
{txt}Ho: mean = {res}0                                     {txt}degrees of freedom = {res}   89741

    {txt}Ha: mean < {res}0                 {txt}Ha: mean != {res}0                 {txt}Ha: mean > {res}0
 {txt}Pr(T < t) = {res}1.0000         {txt}Pr(|T| > |t|) = {res}0.0000          {txt}Pr(T > t) = {res}0.0000

{txt}One-sample t test
{hline 9}{c TT}{hline 68}
Variable{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. Err.{col 47}Std. Dev.{col 59}[95% Conf. Interval]
{hline 9}{c +}{hline 68}
motobike {c |}{res}{col 12} 89,742{col 22} .1298389{col 34}  .001122{col 46} .3361279{col 58} .1276397{col 70} .1320381
{txt}{hline 9}{c BT}{hline 68}
    mean = mean({res}motobike{txt})                                         t = {res}115.7172
{txt}Ho: mean = {res}0                                     {txt}degrees of freedom = {res}   89741

    {txt}Ha: mean < {res}0                 {txt}Ha: mean != {res}0                 {txt}Ha: mean > {res}0
 {txt}Pr(T < t) = {res}1.0000         {txt}Pr(|T| > |t|) = {res}0.0000          {txt}Pr(T > t) = {res}0.0000

{txt}One-sample t test
{hline 9}{c TT}{hline 68}
Variable{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. Err.{col 47}Std. Dev.{col 59}[95% Conf. Interval]
{hline 9}{c +}{hline 68}
   phone {c |}{res}{col 12} 89,742{col 22} .6524704{col 34} .0015896{col 46} .4761883{col 58} .6493549{col 70}  .655586
{txt}{hline 9}{c BT}{hline 68}
    mean = mean({res}phone{txt})                                            t = {res}410.4686
{txt}Ho: mean = {res}0                                     {txt}degrees of freedom = {res}   89741

    {txt}Ha: mean < {res}0                 {txt}Ha: mean != {res}0                 {txt}Ha: mean > {res}0
 {txt}Pr(T < t) = {res}1.0000         {txt}Pr(|T| > |t|) = {res}0.0000          {txt}Pr(T > t) = {res}0.0000

{txt}One-sample t test
{hline 9}{c TT}{hline 68}
Variable{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. Err.{col 47}Std. Dev.{col 59}[95% Conf. Interval]
{hline 9}{c +}{hline 68}
electr~y {c |}{res}{col 12} 89,742{col 22} .3597869{col 34} .0016021{col 46} .4799405{col 58} .3566468{col 70}  .362927
{txt}{hline 9}{c BT}{hline 68}
    mean = mean({res}electricity{txt})                                      t = {res}224.5721
{txt}Ho: mean = {res}0                                     {txt}degrees of freedom = {res}   89741

    {txt}Ha: mean < {res}0                 {txt}Ha: mean != {res}0                 {txt}Ha: mean > {res}0
 {txt}Pr(T < t) = {res}1.0000         {txt}Pr(|T| > |t|) = {res}0.0000          {txt}Pr(T > t) = {res}0.0000

{txt}One-sample t test
{hline 9}{c TT}{hline 68}
Variable{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. Err.{col 47}Std. Dev.{col 59}[95% Conf. Interval]
{hline 9}{c +}{hline 68}
 wagejob {c |}{res}{col 12} 89,742{col 22} .3168528{col 34} .0015531{col 46} .4652521{col 58} .3138088{col 70} .3198968
{txt}{hline 9}{c BT}{hline 68}
    mean = mean({res}wagejob{txt})                                          t = {res}204.0173
{txt}Ho: mean = {res}0                                     {txt}degrees of freedom = {res}   89741

    {txt}Ha: mean < {res}0                 {txt}Ha: mean != {res}0                 {txt}Ha: mean > {res}0
 {txt}Pr(T < t) = {res}1.0000         {txt}Pr(|T| > |t|) = {res}0.0000          {txt}Pr(T > t) = {res}0.0000

{txt}One-sample t test
{hline 9}{c TT}{hline 68}
Variable{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. Err.{col 47}Std. Dev.{col 59}[95% Conf. Interval]
{hline 9}{c +}{hline 68}
enterp~e {c |}{res}{col 12} 89,742{col 22} .4613447{col 34} .0016641{col 46} .4985063{col 58} .4580832{col 70} .4646063
{txt}{hline 9}{c BT}{hline 68}
    mean = mean({res}enterprise{txt})                                       t = {res}277.2380
{txt}Ho: mean = {res}0                                     {txt}degrees of freedom = {res}   89741

    {txt}Ha: mean < {res}0                 {txt}Ha: mean != {res}0                 {txt}Ha: mean > {res}0
 {txt}Pr(T < t) = {res}1.0000         {txt}Pr(|T| > |t|) = {res}0.0000          {txt}Pr(T > t) = {res}0.0000

{txt}One-sample t test
{hline 9}{c TT}{hline 68}
Variable{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. Err.{col 47}Std. Dev.{col 59}[95% Conf. Interval]
{hline 9}{c +}{hline 68}
weathe~k {c |}{res}{col 12} 89,742{col 22} .2062022{col 34} .0013505{col 46} .4045796{col 58} .2035552{col 70} .2088493
{txt}{hline 9}{c BT}{hline 68}
    mean = mean({res}weather_shock{txt})                                    t = {res}152.6818
{txt}Ho: mean = {res}0                                     {txt}degrees of freedom = {res}   89741

    {txt}Ha: mean < {res}0                 {txt}Ha: mean != {res}0                 {txt}Ha: mean > {res}0
 {txt}Pr(T < t) = {res}1.0000         {txt}Pr(|T| > |t|) = {res}0.0000          {txt}Pr(T > t) = {res}0.0000

{txt}One-sample t test
{hline 9}{c TT}{hline 68}
Variable{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. Err.{col 47}Std. Dev.{col 59}[95% Conf. Interval]
{hline 9}{c +}{hline 68}
plot_a~a {c |}{res}{col 12} 89,742{col 22} 1.404158{col 34} .0181099{col 46}  5.42518{col 58} 1.368663{col 70} 1.439653
{txt}{hline 9}{c BT}{hline 68}
    mean = mean({res}plot_area{txt})                                        t = {res} 77.5353
{txt}Ho: mean = {res}0                                     {txt}degrees of freedom = {res}   89741

    {txt}Ha: mean < {res}0                 {txt}Ha: mean != {res}0                 {txt}Ha: mean > {res}0
 {txt}Pr(T < t) = {res}1.0000         {txt}Pr(|T| > |t|) = {res}0.0000          {txt}Pr(T > t) = {res}0.0000

{txt}One-sample t test
{hline 9}{c TT}{hline 68}
Variable{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. Err.{col 47}Std. Dev.{col 59}[95% Conf. Interval]
{hline 9}{c +}{hline 68}
other_~p {c |}{res}{col 12} 89,742{col 22} .1920171{col 34} .0013148{col 46} .3938887{col 58}   .18944{col 70} .1945942
{txt}{hline 9}{c BT}{hline 68}
    mean = mean({res}other_crop{txt})                                       t = {res}146.0375
{txt}Ho: mean = {res}0                                     {txt}degrees of freedom = {res}   89741

    {txt}Ha: mean < {res}0                 {txt}Ha: mean != {res}0                 {txt}Ha: mean > {res}0
 {txt}Pr(T < t) = {res}1.0000         {txt}Pr(|T| > |t|) = {res}0.0000          {txt}Pr(T > t) = {res}0.0000

{txt}One-sample t test
{hline 9}{c TT}{hline 68}
Variable{col 10}{c |}{col 16}Obs{col 27}Mean{col 35}Std. Err.{col 47}Std. Dev.{col 59}[95% Conf. Interval]
{hline 9}{c +}{hline 68}
dist_p~r {c |}{res}{col 12} 61,916{col 22} 31.32904{col 34} .1359641{col 46} 33.83185{col 58} 31.06255{col 70} 31.59553
{txt}{hline 9}{c BT}{hline 68}
    mean = mean({res}dist_popcenter{txt})                                   t = {res}230.4214
{txt}Ho: mean = {res}0                                     {txt}degrees of freedom = {res}   61915

    {txt}Ha: mean < {res}0                 {txt}Ha: mean != {res}0                 {txt}Ha: mean > {res}0
 {txt}Pr(T < t) = {res}1.0000         {txt}Pr(|T| > |t|) = {res}0.0000          {txt}Pr(T > t) = {res}0.0000
{txt}
{com}. 
. matrix rownames Y =  hhsize dependent_share head_age female_head head_read  motobike phone  electricity wagejob enterprise weather_shock  plot_area other_crop dist_popcenter
{txt}
{com}. 
. matrix colnames Y =  mean sd
{txt}
{com}. 
. matrix list Y
{res}
{txt}Y[100,5]
                   mean         sd         sd         sd         sd
      hhsize {res} 5.3640436  2.9701844          .          .          .
{txt}dependent_~e {res} .44830053    .248803          .          .          .
{txt}    head_age {res} 46.535669  15.582635          .          .          .
{txt} female_head {res} .25146531  .43385782          .          .          .
{txt}   head_read {res} .64839206  .47747496          .          .          .
{txt}    motobike {res} .12983887  .33612795          .          .          .
{txt}       phone {res} .65247042   .4761883          .          .          .
{txt} electricity {res} .35978694  .47994048          .          .          .
{txt}     wagejob {res} .31685276  .46525208          .          .          .
{txt}  enterprise {res} .46134474  .49850631          .          .          .
{txt}weather_sh~k {res} .20620222  .40457965          .          .          .
{txt}   plot_area {res} 1.4041578  5.4251798          .          .          .
{txt}  other_crop {res} .19201712  .39388865          .          .          .
{txt}dist_popce~r {res} 31.329044  33.831847          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{txt}dist_popce~r {res}         .          .          .          .          .
{reset}
{com}. frmttable using S19.doc, replace  statmat(Y) ctitle("", "mean", "sd") sdec(2)
{res}{txt:(note: file S19.doc not found)}
{txt}{center:{hline 39}}
{center:{txt}{lalign 17:}{txt}{center 7:mean}{txt}{center 7:sd}{txt}{center 2:}{txt}{center 2:}{txt}{center 2:}}
{txt}{center:{hline 39}}
{center:{txt}{lalign 17:hhsize}{res}{center 7:5.36}{res}{center 7:2.97}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dependent_share}{res}{center 7:0.45}{res}{center 7:0.25}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:head_age}{res}{center 7:46.54}{res}{center 7:15.58}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:female_head}{res}{center 7:0.25}{res}{center 7:0.43}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:head_read}{res}{center 7:0.65}{res}{center 7:0.48}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:motobike}{res}{center 7:0.13}{res}{center 7:0.34}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:phone}{res}{center 7:0.65}{res}{center 7:0.48}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:electricity}{res}{center 7:0.36}{res}{center 7:0.48}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:wagejob}{res}{center 7:0.32}{res}{center 7:0.47}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:enterprise}{res}{center 7:0.46}{res}{center 7:0.50}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:weather_shock}{res}{center 7:0.21}{res}{center 7:0.40}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:plot_area}{res}{center 7:1.40}{res}{center 7:5.43}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:other_crop}{res}{center 7:0.19}{res}{center 7:0.39}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:31.33}{res}{center 7:33.83}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{center:{txt}{lalign 17:dist_popcenter}{res}{center 7:}{res}{center 7:}{res}{center 2:}{res}{center 2:}{res}{center 2:}}
{txt}{center:{hline 39}}


{com}. restore
{txt}
{com}. log close
      {txt}name:  {res}<unnamed>
       {txt}log:  {res}C:\lSMS ISA\dofile\Submission\S1_S9_and_S19.smcl
  {txt}log type:  {res}smcl
 {txt}closed on:  {res} 5 Apr 2024, 11:02:35
{txt}{.-}
{smcl}
{txt}{sf}{ul off}